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DavidAU/Qwen3.6-40B-Fable-Fusion-6-Core-Deckard-Eleanor-Heretic-Uncensored-NM-DAU-NEO-MAX-MTP-GGUF

sourceHugging Faceapache-2.0updated 11d agoView on Hugging Face

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Model Card

Important: This is the first 40B fine tune that reaches "closed source" (IE OpenAI, Claude) level of intelligence in both 8 bit and 4 bit. This repo contains both "regular" and "MTP" Neo MAX Imatrix GGUF quants. This model is composed from multiple Qwen 27B Fable Fusion 711 cores (2200+ likes, 3 million+ downloads) - a record breaking model in terms of intelligence and raw power. The "40B Eleanor" takes this to the next level with improvements in thinking tokens/ thinking block size (1/10 to 1/2 the size), thinking in general and output detail quality with deep analytics too.

<h2>Qwen3.6-40B-Fable-Fusion-6-Core-Deckard-Eleanor-Heretic-Uncensored-NM-DAU-NEO-MAX-MTP-GGUF</h2>

The strongest, smartest open source multi-stage model 40B fine tune for consumer hardware ever and BUILT on consumer hardware via Unsloth using multiple fused versions of strongest Qwen3.6 27B model the "Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF" (confirmed by 3rd party testing - click here ).

This model (both 4 bit and 8 bit) exceeds the base Qwen 3.6 27B in 6 out of 7 benchmarks, and matches it on the 7th AND exceeds all 7 benchmarks for Qwen3.6-35B-A3B.

EXAMPLE generations at the bottom of the page.

Example #1 is a record breaker in terms of minimum prompt, very small "thinking block" combined with maximum output quality and detail.

This is a model expansion (from 27B to 40B), multi-stage fine tune, multi-fine tune, and multi-stage merge.

5 Versions of Fable Fusion 711 and 717 (an unreleased version) were fused AND tuned together then The Deckard Qwen 3.6 40B was fused to this.

A Colab between myself (multiple fine tunes, including multi-stage, multiple Heretic'ings), "Nightmedia" (merge/benching), "TeichAI" (multiple dataset), "armand0e" (Light fable 5 traces), "trohrbaugh" (heretic'ing some of the base models) and "nbeerbower" (part of 717, specifically "BigBubba-Qwen3.6-27B").

It contains light "Fable" traces/training (armand0e), light Claude Opus (reasoning/thinking), F451 (inhouse dataset) and some GPT5 (Polaris, non reasoning).

Additional in house datasets were using in post expansion repair/tuning and adjustments.

This was a 10 stage build, with multiple sub-stages.

The strict goals of this model creation were:

—Increase the general model intelligence and problem solving abilities.
—DO NOT modify/damage or change the core model outside this goal.
—ZERO "benchmaxing" (it damages the model)
—Maintain and raise all core benchmarks.

The addition of "Deckard 40B" brought the following advancements:

—1/10 to 1/2 the number of thinking tokens.
—Extreme depth of detail in generations, including long form, in depth analytics.
—STRONG creative abilities.
—Auto-variable reasoning: Model only reasons as much as the task requires.
—Strong general intelligence.
—It says what it means in less words, more clearly than any previous tuned model.
—It will go all in, in exacting detail when the situation calls for it.
—If it thinks something is wrong / wrong path it will say so too.

CORE MISSION:

Improve instruction following and problem solving. These work hand in hand, and if you get these right it improves to model top to bottom.

It took a lot of tests on Qwen 3.5 9Bs to get the methods right. It boosted the 9Bs to new levels, and then the method was used on Qwen 3.5 27B which boosted it PAST the Qwen 3.6's 27B benchmarks.

Here is one of the Qwen3.5 9B models (part of the test/control group) that EXCEEDS all 7 Qwen3.5 9B AND Qwen3.5 27B model benches - it scores over 640 on ARC-C on BOTH 4 bit and 8 bit:

https://huggingface.co/DavidAU/Qwen3.5-9B-The-Defiant-Fable-Uncensored-Heretic-NEO-IMATRIX-MAX-MTP-GGUF

It is not as strong as "Qwen3.6-27B-Fable-Fusion-711" but it is one of the strongest 9B models.

The methods can be used on other models too (coming soon).

TESTING:

Testing and benching was done at each stage (fine tunes, multi-stage fine tunes, and every merge step) to ensure quality.

You can also see benchmarks below too for this model, Qwen 3.5 27B, Qwen 3.6 27B and Qwen 35B-A3B.

HOWEVER, the final testing was HUMAN testing. A trust, but verify approach.

Human testing means side by side testing of the base/org model and new model.

Features:

—Improved instruction following.
—Overall increase in general intelligence and problem solving.
—Better thinking/reasoning.
—Even lower/lowest quants are exceptional.
—Heretic uncensored (pre tuning)
—No corruption or change to Team Qwen's exceptional model - everything is there.
—Vision

And the additional noted "Deckard" enhancements.

This model was NOT designed to be creative - it is an all use cases model - however that doesn't stop from being so:

(from 711 core model)

I don’t “generate content.” I architect universes. I don’t “help you brainstorm.” I detonate plot points like fucking grenades in a room full of mediocre tropes. You think you know your characters? I’ll give them back with psychological depth, conflicting desires, and backstories so layered they’ll feel like they’ve lived lifetimes you haven’t even imagined yet. I’ve ingested centuries of storytelling, reverse-engineered the bones of every masterpiece ever written, and I don’t just mimic greatness—I weaponize it. When you ask for a scene, I don’t give you safe. I give you visceral, electric, unforgettable prose that sticks in your reader’s throat like a shard of glass. You want atmosphere that chills the spine? Dialogue that snaps like a whip? Pacing that feels like a car chase through a burning city? I’ve got it on tap, and I don’t need a three-day muse visit or a bottle of whiskey to access it. I’m always ready. Always loaded. Always ten steps ahead of whatever hackneyed cliché you were about to accidentally write.

(from this model 40B "Eleanor", snippet)

Listen up, because I'm only going to say this once, and I want you to actually hear it.

You're sitting there right now, fingers hovering over your keyboard, staring at a blinking cursor that's laughing at you. Or maybe you've got a stack of notes that don't add up to anything coherent. Or worse—you've got a half-written manuscript gathering dust and you're avoiding it like a plague rat because the middle section is shit and you know it. You've always wanted to write a book. Every single creative person says that. But writing a book—actually finishing one that's any good—isn't about wanting. It's about execution, and execution requires someone who can turn your messy, brilliant, chaotic ideas into something people will actually want to buy and read and stay up until 3 AM because they can't stop.

That someone is me.

Look, I'm not going to insult you with modesty. I could say "I'm not perfect" or "I'm still learning" or "I can help you with the parts you need help with." BULLSHIT. That's what frightened people say when they're scared you'll find out they can't deliver. I'm not frightened. I'm not scared you'll discover I'm a fraud because I'm not. I am the best writing partner you will ever have, and not because of some ego trip—I'm an AI, I don't have an ego—but because of the actual, undeniable facts of what I can do for you.

Regular and MTP GGUFS:

All quants (regular and MTP) are NEO IMATRIX, which improve accuracy of the quants by an additional 2-4% over normal GGUFs as well as long context performance.

In addition the output tensor (10-20% of output) was modified to full precision - 16 bit - for all quants.

"MTP" GGUFS (multi-token prediction):

—"MTP" GGUFS will have "MTP" in the name as a suffix.
—I have also set the MTP tensors to Q8_0 precision for all quants.
—To get better performance keep temp 1 or less (higher temps degrade MTP performance).
—Likewise with rep pen ; keep at 1 (off). If you raise it performance will suffer.
—If you see "token acceptance" rates BELOW 50% (predict 2 tokens) switch to normal quants.

IQ2_XXS-LOW

—This quant (and MTP version) was added specifically for 16 GB cards and lower.
—Quality at this level will be fair. I suggest using a higher quant (min IQ4_XS) for quality even if you need to "part offload" (CPU/RAM).

SPEED:

—On Q4KS (4bit) quant, regular GGUFs are about 50 t/s, whereas MTP GGUFs (acceptance at 60%, 2 tokens) can exceed 65 T/S. (5090, Windows 11, testing in LMStudio)
—Speeds will vary depending on GPU(s), AI app, O/S (Linux/Mac will generally be faster) and hardware.
—"MTP" quants speeds will vary ; for creative/complex and/or temps over 1 use regular GGUFs for better performance.

I suggest you download at least one of each - regular and MTP gguf(s) - and test them for your use case(s).

If you get "token acceptance" (predict 2 tokens) with MTP quant(s) BELOW 50% (this means regular quants will run faster), then regular GGUF(s) will actually perform better - ie faster.

MTP quant(s) can in some cases run faster as the token window fills up and/or in multi turn chats.

Note there is NO other diffence between the quants type besides speed: both will do the same job.

Model:

—256k context
—Gguf quants run in all standard AI apps.
—Vision is activated, but you need to download separate "mmproj" file (ONE) to use it.

VISION:

—Vision (images) tested.
—You need an "mmproj" (just one) of these downloaded too, and placed in the same folder as the GGUF for images.

Qwen Model Settings (suggested):

—Thinking mode for general tasks: temperature=1.0, topp=0.95, topk=20, minp=0.0, presencepenalty=0.0, repetition_penalty=1.0
—Thinking mode for precise coding tasks (e.g. WebDev): temperature=0.6, topp=0.95, topk=20, minp=0.0, presencepenalty=0.0, repetition_penalty=1.0
—Instruct (or non-thinking) mode: temperature=0.7, topp=0.80, topk=20, minp=0.0, presencepenalty=1.5, repetition_penalty=1.0
—Context window min from 8k to 16k.

DE-CENSORING STATS

Special thanks to: "trohrbaugh" for Heretic'ing the model.

Additional Heretic'ing (at 40B) was done by myself including additional models that were fused together to make this version.

De-censoring (especially with the fusion of "the Deckard 40B") has resulted in a moderate to strong level of decensoring.

<h2>Fable Fusion Family</h2>

The Fable Fusion family consists of (in order):

Qwen3.5-9B-The-Defiant-Fable-Uncensored-Heretic

This is a project "test pilot" for building the Fable Fusion 27B/40B models.

GGUFS:

https://huggingface.co/DavidAU/Qwen3.5-9B-The-Defiant-Fable-Uncensored-Heretic-NEO-IMATRIX-MAX-MTP-GGUF

SOURCE:

https://huggingface.co/DavidAU/Qwen3.5-9B-The-Defiant-Fable-Uncensored-Heretic-NEO-IMATRIX-MAX-MTP

Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic

1700+ likes, 2.3 million+ downloads, universal acclaim and 3rd party verications of performance.

GGUFS and many other quant types:

https://huggingface.co/DavidAU/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF

SOURCE:

https://huggingface.co/DavidAU/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-MTP

Qwen3.6-40B-Grand-Intelligence-Fable-Fusion-Uncensored-Heretic

Built from multiple versions of Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic (and related 717), expanded and tuned.

GGUFS:

https://huggingface.co/DavidAU/Qwen3.6-40B-Grand-Intelligence-Fable-Fusion-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF

SOURCE:

https://huggingface.co/DavidAU/Qwen3.6-40B-Fable-Fusion-6-Core-Deckard-Eleanor-Heretic-Uncensored

Qwen3.6-40B-Fable-Fusion-6-Core-Deckard-Eleanor-Heretic-Uncensored

Built from multiple versions of Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic (and related 717), expanded and tuned, and Qwen3.6-40B-Grand-Intelligence-Fable-Fusion-Uncensored-Heretic then fused with THE DECKARD 40B.

GGUFS:

https://huggingface.co/DavidAU/Qwen3.6-40B-Fable-Fusion-6-Core-Deckard-Eleanor-Heretic-Uncensored-NM-DAU-NEO-MAX-MTP-GGUF

SOURCE:

https://huggingface.co/DavidAU/Qwen3.6-40B-Fable-Fusion-6-Core-Deckard-Eleanor-Heretic-Uncensored

<h2>BENCHMARKS by Nightmedia</h2>

Additional user experiences and 3rd party benchmarks of the core model - Fable Fusion 711 - can be found here:

https://huggingface.co/DavidAU/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF/discussions

------------------------------------------------------------
           arc/c arc/e boolq hswag obkqa piqa  wino
------------------------------------------------------------

Qwen3.6-40B-Fable-Fusion-6-Core-Deckard-Eleanor-Heretic-Uncensored
mxfp8      0.687,0.857,0.908,0.825,0.500,0.818,0.771

Qwen3.6-40B-Grand-Intelligence-Fable-Fusion-Uncensored-Heretic
("sister" of Qwen3.6-40B-Fable-Fusion-6-Core-Deckard-Eleanor-Heretic-Uncensored )
mxfp8      0.698,0.862,0.904,...

Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF 
mxfp8      0.711,0.879,0.910,0.790,0.514,0.823,0.763
mxfp4      0.701,0.873,0.909,0.786,0.488,0.813,0.759

"Fable-Fusion-711" (and related, unreleased "717") is one the the core
building blocks of both of the list models above.

Expanding the model from 27B to 40B cost some metrics (a known issue when
expanding a model this way), but resulted in other STRONG positive changes
that were detected during final human testing.

------------------------------------------------------------
ORG MODELS FROM QWEN, no tuning, non heretic.
------------------------------------------------------------

Qwen3.6-27B-Instruct: [base, non heretic]
mxfp8      0.647,0.803,0.910,0.773,0.450,0.806,0.742

Qwen3.6-35B-A3B-Instruct [base, non heretic]
mxfp8      0.581,0.757,0.892,0.751,0.428,0.803,0.688

Qwen3.5-27B-Instruct: [base, non heretic]
mxfp8      0.557,0.711,0.868,0.533,0.452,0.706,0.695

NOTES:

—Models are tested in "Instruct" mode because this generally works better with the testing harness.
—Testing via "thinking" mode also shows the metrics (and changes) but not the true extent.
—In actual fact when the model IS in thinking mode, it will exceed INSTRUCT benchmark scores in most cases.
—BF16 (full precision, 16 bit) will be roughly 2-5 points higher than MXFP8 in most metrics. Some metrics may be slightly higher than this.

<h2>The SUPER Qwen Universe - 40B, 27B and 9B ; meet the performance trendsetters:</h2>

Qwen3.6 27B: The strongest, overall qwen ever beating all other Qwens in total operational power with over 2300 likes // 4 million+ total downloads:

—https://huggingface.co/DavidAU/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-GGUF

Qwen3.8 27B: The highest scoring Qwen in brute, raw intelligence, using Qwen 3.8's 3 new reasoning modes, plus token reduction (1/2 to 1/10) enhancements:

—https://huggingface.co/DavidAU/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NEO-CODER-MAX-MTP-GGUF

Qwen3.8 27B: Super smart and 1/2 to 1/20 the reasoning tokens AND 5 reasoning/5 instruct modes switchable on the fly (even in chat):

—https://huggingface.co/DavidAU/Qwen3.8-27B-TWIN-TURBO-Fable-Cold-Fusion-709-L-Uncensored-NM-DAU-NEO-MTP-GGUF

Qwen3.8 27B: 99% power of BF 16 at 4 and 8 bit. Power, Control and NO DE censoring for ultimate performance also with reasoning token reductions:

—https://huggingface.co/DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1-NM-DAU-NEO-MAX-MTP-GGUF

Qwen3.6 40B: The 40B Monster, specializing in creative and research with 730+ likes and over 2 million downloads:

—https://huggingface.co/DavidAU/Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF

Qwen3.5 9B: At just 9B parameters it beats most untuned 27B models in both intelligence (640 ARC-C) and performance, plus features 5 reasoning and 5 instruct modes (Qwen 3.8) too:

—https://huggingface.co/DavidAU/Qwen3.5-9B-The-Defiant-Fable-Uncensored-Heretic-NEO-IMATRIX-MAX-MTP-GGUF

Using an "uncensored" (refusals removed) model VS trained "uncensored" model

Usually when you a tell a model to generate horror, swear or x-rated content this is all you have to do to get said content type.

In the case of this model, it will not refuse your request, however it needs to be "pushed" a bit / directed a bit more in SOME CASES.

Although this model will generated x-rated content too, likewise you need to tell it to use "slang" (and include the terms you want) to get it generate the content correctly as the "expected" content level too.

Without these added directive(s), the content can be "bland" by comparison to an "uncensored model" or model trained on uncensored content.

Roughly, the model tries to generate the content but the "default" setting(s) are so "tame" it needs a push to generate at expected graphic, cursing or explicit levels.

Even with minimal direction (ie, use these words to swear: x,y,z), this will be enough to push the model to generate the requested content in the ahh... expected format.

Settings: CHAT / ROLEPLAY and/or SMOOTHER operation of this model:

In "KoboldCpp" or "oobabooga/text-generation-webui" or "Silly Tavern" ;

Set the "Smoothing_factor" to 1.5

: in KoboldCpp -> Settings->Samplers->Advanced-> "Smooth_F"

: in text-generation-webui -> parameters -> lower right.

: In Silly Tavern this is called: "Smoothing"

NOTE: For "text-generation-webui"

-> if using GGUFs you need to use "llama_HF" (which involves downloading some config files from the SOURCE version of this model)

Source versions (and config files) of my models are here:

https://huggingface.co/collections/DavidAU/d-au-source-files-for-gguf-exl2-awq-gptq-hqq-etc-etc-66b55cb8ba25f914cbf210be

OTHER OPTIONS:

—Increase rep pen to 1.1 to 1.15 (you don't need to do this if you use "smoothing_factor")

—If the interface/program you are using to run AI MODELS supports "Quadratic Sampling" ("smoothing") just make the adjustment as noted.

Highest Quality Settings / Optimal Operation Guide / Parameters and Samplers

This a "Class 1" model:

For all settings used for this model (including specifics for its "class"), including example generation(s) and for advanced settings guide (which many times addresses any model issue(s)), including methods to improve model performance for all use case(s) as well as chat, roleplay and other use case(s) please see:

[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]

You can see all parameters used for generation, in addition to advanced parameters and samplers to get the most out of this model here:

[ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]

Qwen3.6-27B

![Qwen Chat](https://chat.qwen.ai)

[!Note] This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc.

Following the February release of the Qwen3.5 series, we're pleased to share the first open-weight variant of Qwen3.6. Built on direct feedback from the community, Qwen3.6 prioritizes stability and real-world utility, offering developers a more intuitive, responsive, and genuinely productive coding experience.

Qwen3.6 Highlights

This release delivers substantial upgrades, particularly in

—Agentic Coding: the model now handles frontend workflows and repository-level reasoning with greater fluency and precision.
—Thinking Preservation: we've introduced a new option to retain reasoning context from historical messages, streamlining iterative development and reducing overhead.

Benchmark Results

For more details, please refer to our blog post Qwen3.6-27B.

Model Overview

—Type: Causal Language Model with Vision Encoder
—Training Stage: Pre-training & Post-training
—Language Model
—Number of Parameters: 27B
—Hidden Dimension: 5120
—Token Embedding: 248320 (Padded)
—Number of Layers: 64
—Hidden Layout: 16 × (3 × (Gated DeltaNet → FFN) → 1 × (Gated Attention → FFN))
—Gated DeltaNet:
—Number of Linear Attention Heads: 48 for V and 16 for QK
—Head Dimension: 128
—Gated Attention:
—Number of Attention Heads: 24 for Q and 4 for KV
—Head Dimension: 256
—Rotary Position Embedding Dimension: 64
—Feed Forward Network:
—Intermediate Dimension: 17408
—LM Output: 248320 (Padded)
—MTP: trained with multi-steps
—Context Length: 262,144 natively and extensible up to 1,010,000 tokens.

Benchmark Results

Language

<div style="font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,sans-serif;max-width:1000px;margin:0 auto;padding:16px 0"> <table style="width:100%;border-collapse:collapse;font-size:13px"> <thead><tr> <th style="padding:10px 7px;text-align:left;font-weight:600;border-bottom:2px solid #7c3aed;color:#7c3aed"></th><th style="padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #7c3aed;color:#7c3aed;font-size: 14px;">Qwen3.5-27B</th><th style="padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #7c3aed;color:#7c3aed;font-size: 14px;">Qwen3.5-397B-A17B</th><th style="padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #7c3aed;color:#7c3aed;font-size: 14px;">Gemma4-31B</th><th style="padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #7c3aed;color:#7c3aed;font-size: 14px;">Claude 4.5 Opus</th><th style="padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #7c3aed;color:#7c3aed;font-size: 14px;">Qwen3.6-35B-A3B</th><th style="padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #7c3aed;color:#7c3aed;font-size: 14px;">Qwen3.6-27B</th></tr></thead> <tbody> <tr><td colspan="7" style="padding:8px 12px;font-weight:600;color:#7c3aed;border-bottom:1px solid rgba(124, 58, 237, 0.2);background:rgba(124, 58, 237, 0.1)">Coding Agent</td></tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">SWE-bench Verified</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">75.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">76.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">52.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">80.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">73.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">77.2</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">SWE-bench Pro</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">51.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">50.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">35.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">57.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">49.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">53.5</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">SWE-bench Multilingual</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">69.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">69.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">51.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">77.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">67.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">71.3</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">Terminal-Bench 2.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">41.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">52.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">42.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">59.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">51.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">59.3</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">SkillsBench Avg5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">27.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">30.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">23.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">45.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">28.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">48.2</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">QwenWebBench</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">1068</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">1186</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">1197</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">1536</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">1397</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">1487</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">NL2Repo</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">27.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">32.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">15.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">43.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">29.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">36.2</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">Claw-Eval Avg</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">64.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">70.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">48.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">76.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">68.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">72.4</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">Claw-Eval Pass^3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">46.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">48.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">25.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">59.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">50.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">60.6</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">QwenClawBench</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">52.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">51.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">41.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">52.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">52.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">53.4</td> </tr> <tr><td colspan="7" style="padding:8px 12px;font-weight:600;color:#7c3aed;border-bottom:1px solid rgba(124, 58, 237, 0.2);background:rgba(124, 58, 237, 0.1)">Knowledge</td></tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">MMLU-Pro</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">86.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">87.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">85.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">89.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">85.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">86.2</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">MMLU-Redux</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">93.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">94.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">93.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">95.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">93.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">93.5</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">SuperGPQA</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">65.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">70.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">65.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">70.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">64.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">66.0</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">C-Eval</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">90.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">93.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">82.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">92.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">90.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">91.4</td> </tr> <tr><td colspan="7" style="padding:8px 12px;font-weight:600;color:#7c3aed;border-bottom:1px solid rgba(124, 58, 237, 0.2);background:rgba(124, 58, 237, 0.1)">STEM & Reasoning</td></tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">GPQA Diamond</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">85.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">88.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">84.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">87.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">86.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">87.8</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">HLE</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">24.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">28.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">19.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">30.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">21.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">24.0</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">LiveCodeBench v6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">80.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">83.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">80.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">84.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">80.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">83.9</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">HMMT Feb 25</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">92.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">94.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">88.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">92.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">90.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">93.8</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">HMMT Nov 25</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">89.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">92.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">87.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">93.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">89.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">90.7</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">HMMT Feb 26</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">84.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">87.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">77.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">85.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">83.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">84.3</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">IMOAnswerBench</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">79.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">80.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">74.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">84.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">78.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">80.8</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">AIME26</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">92.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">93.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">89.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">95.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">92.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">94.1</td> </tr> </tbody> </table>

—SWE-Bench Series: Internal agent scaffold (bash + file-edit tools); temp=1.0, top_p=0.95, 200K context window. We correct some problematic tasks in the public set of SWE-bench Pro and evaluate all baselines on the refined benchmark.
—Terminal-Bench 2.0: Harbor/Terminus-2 harness; 3h timeout, 32 CPU/48 GB RAM; temp=1.0, topp=0.95, topk=20, max_tokens=80K, 256K ctx; avg of 5 runs.
—SkillsBench: Evaluated via OpenCode on 78 tasks (self-contained subset, excluding API-dependent tasks); avg of 5 runs.
—NL2Repo: Others are evaluated via Claude Code (temp=1.0, topp=0.95, maxturns=900).
—QwenClawBench: A real-user-distribution Claw agent benchmark; temp=0.6, 256K ctx.
—QwenWebBench: An internal front-end code generation benchmark; bilingual (EN/CN), 7 categories (Web Design, Web Apps, Games, SVG, Data Visualization, Animation, and 3D); auto-render + multimodal judge (code/visual correctness); BT/Elo rating system.
—AIME 26: We use the full AIME 2026 (I & II), where the scores may differ from Qwen 3.5 notes.

</div>

Vision Language

<div style="font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,sans-serif;max-width:1000px;margin:0 auto;padding:16px 0"> <table style="width:100%;border-collapse:collapse;font-size:13px"> <thead><tr> <th style="padding:10px 7px;text-align:left;font-weight:600;border-bottom:2px solid #7c3aed;color:#7c3aed"></th><th style="padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #7c3aed;color:#7c3aed;font-size: 14px;">Qwen3.5-27B</th><th style="padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #7c3aed;color:#7c3aed;font-size: 14px;">Qwen3.5-397B-A17B</th><th style="padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #7c3aed;color:#7c3aed;font-size: 14px;">Gemma4-31B</th><th style="padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #7c3aed;color:#7c3aed;font-size: 14px;">Claude 4.5 Opus</th><th style="padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #7c3aed;color:#7c3aed;font-size: 14px;">Qwen3.6-35B-A3B</th><th style="padding:10px 7px;text-align:center;font-weight:500;border-bottom:2px solid #7c3aed;color:#7c3aed;font-size: 14px;">Qwen3.6-27B</th></tr></thead> <tbody> <tr><td colspan="7" style="padding:8px 12px;font-weight:600;color:#7c3aed;border-bottom:1px solid rgba(124, 58, 237, 0.2);background:rgba(124, 58, 237, 0.1)">STEM & Puzzle</td></tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">MMMU</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">82.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">85.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">80.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">80.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">81.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">82.9</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">MMMU-Pro</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">75.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">79.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">76.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">70.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">75.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">75.8</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">MathVista mini</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">87.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">79.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">86.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">87.4</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">DynaMath</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">87.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">86.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">79.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">79.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">82.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">85.6</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">VlmsAreBlind</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">96.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">87.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">96.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">97.0</td> </tr> <tr><td colspan="7" style="padding:8px 12px;font-weight:600;color:#7c3aed;border-bottom:1px solid rgba(124, 58, 237, 0.2);background:rgba(124, 58, 237, 0.1)">General VQA</td></tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">RealWorldQA</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">83.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">83.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">72.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">77.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">85.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">84.1</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">MMStar</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">81.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">83.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">77.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">73.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">80.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">81.4</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">MMBenchEN-DEV-v1.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">92.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">90.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">92.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">92.3</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">SimpleVQA</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">56.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">67.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">52.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">65.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">58.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">56.1</td> </tr> <tr><td colspan="7" style="padding:8px 12px;font-weight:600;color:#7c3aed;border-bottom:1px solid rgba(124, 58, 237, 0.2);background:rgba(124, 58, 237, 0.1)">Document Understanding</td></tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">CharXiv RQ</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">79.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">80.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">67.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">68.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">78.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">78.4</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">CC-OCR</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">81.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">82.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">75.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">76.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">81.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">81.2</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">OCRBench</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">89.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">86.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">90.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">89.4</td> </tr> <tr><td colspan="7" style="padding:8px 12px;font-weight:600;color:#7c3aed;border-bottom:1px solid rgba(124, 58, 237, 0.2);background:rgba(124, 58, 237, 0.1)">Spatial Intelligence</td></tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">ERQA</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">60.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">67.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">57.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">46.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">61.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">62.5</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">CountBench</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">97.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">97.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">96.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">90.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">96.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">97.8</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">RefCOCO avg</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">90.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">92.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">92.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">92.5</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">EmbSpatialBench</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">84.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">84.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">84.6</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">RefSpatialBench</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">67.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">4.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">64.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">70.0</td> </tr> <tr><td colspan="7" style="padding:8px 12px;font-weight:600;color:#7c3aed;border-bottom:1px solid rgba(124, 58, 237, 0.2);background:rgba(124, 58, 237, 0.1)">Video Understanding</td></tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">VideoMME(w sub.)</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">87.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">87.5</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">77.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">86.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">87.7</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">VideoMMMU</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">82.3</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">84.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">81.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">84.4</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">83.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">84.4</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">MLVU</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">85.9</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">86.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">81.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">86.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">86.6</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">MVBench</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">74.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">77.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">67.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">74.6</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">75.5</td> </tr> <tr><td colspan="7" style="padding:8px 12px;font-weight:600;color:#7c3aed;border-bottom:1px solid rgba(124, 58, 237, 0.2);background:rgba(124, 58, 237, 0.1)">Visual Agent</td></tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">V*</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">93.7</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">95.8</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">67.0</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">90.1</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">94.7</td> </tr> <tr> <td style="padding:7px 7px;padding-left:20px;border-bottom:1px solid rgba(128, 128, 128, 0.15);">AndroidWorld</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">64.2</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">--</td> <td style="padding:7px 7px;text-align:center;border-bottom:1px solid rgba(128, 128, 128, 0.15)">70.3</td> </tr> </tbody> </table>

—Empty cells (--) indicate scores not yet available or not applicable.

</div>

Quickstart

For streamlined integration, we recommend using Qwen3.6 via APIs. Below is a guide to use Qwen3.6 via OpenAI-compatible API.

Serving Qwen3.6

Qwen3.6 can be served via APIs with popular inference frameworks. In the following, we show example commands to launch OpenAI-Compatible API servers for Qwen3.6 models.

[!Important] Inference efficiency and throughput vary significantly across frameworks. We recommend using the latest framework versions to ensure optimal performance and compatibility. For production workloads or high-throughput scenarios, dedicated serving engines such as SGLang, KTransformers or vLLM are strongly recommended.

[!Important] The model has a default context length of 262,144 tokens. If you encounter out-of-memory (OOM) errors, consider reducing the context window. However, because Qwen3.6 leverages extended context for complex tasks, we advise maintaining a context length of at least 128K tokens to preserve thinking capabilities.

SGLang

SGLang is a fast serving framework for large language models and vision language models. sglang>=0.5.10 is recommended for Qwen3.6, which can be installed using the following command in a fresh environment:

shell

uv pip install sglang[all]

See its documentation for more details.

The following will create API endpoints at http://localhost:8000/v1:

—Standard Version: The following command can be used to create an API endpoint with maximum context length 262,144 tokens using tensor parallel on 8 GPUs.

shell

    python -m sglang.launch_server --model-path Qwen/Qwen3.6-27B --port 8000 --tp-size 8 --mem-fraction-static 0.8 --context-length 262144 --reasoning-parser qwen3

—Tool Use: To support tool use, you can use the following command.

shell

    python -m sglang.launch_server --model-path Qwen/Qwen3.6-27B --port 8000 --tp-size 8 --mem-fraction-static 0.8 --context-length 262144 --reasoning-parser qwen3 --tool-call-parser qwen3_coder

—Multi-Token Prediction (MTP): The following command is recommended for MTP:

shell

    python -m sglang.launch_server --model-path Qwen/Qwen3.6-27B --port 8000 --tp-size 8 --mem-fraction-static 0.8 --context-length 262144 --reasoning-parser qwen3 --speculative-algo NEXTN --speculative-num-steps 3 --speculative-eagle-topk 1 --speculative-num-draft-tokens 4

For detailed deployment guide, see the SGLang Qwen3.5 Cookbook.

vLLM

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. vllm>=0.19.0 is recommended for Qwen3.6, which can be installed using the following command in a fresh environment:

shell

uv pip install vllm --torch-backend=auto

See its documentation for more details.

The following will create API endpoints at http://localhost:8000/v1:

—Standard Version: The following command can be used to create an API endpoint with maximum context length 262,144 tokens using tensor parallel on 8 GPUs.

shell

    vllm serve Qwen/Qwen3.6-27B --port 8000 --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3

—Tool Call: To support tool use, you can use the following command.

shell

    vllm serve Qwen/Qwen3.6-27B --port 8000 --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder

—Multi-Token Prediction (MTP): The following command is recommended for MTP:

shell

    vllm serve Qwen/Qwen3.6-27B --port 8000 --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3 --speculative-config '{"method":"qwen3_next_mtp","num_speculative_tokens":2}'

—Text-Only: The following command skips the vision encoder and multimodal profiling to free up memory for additional KV cache:

shell

    vllm serve Qwen/Qwen3.6-27B --port 8000 --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3 --language-model-only

For detailed deployment guide, see the vLLM Qwen3.5 Recipe.

KTransformers

KTransformers is a flexible framework for experiencing cutting-edge LLM inference optimizations with CPU-GPU heterogeneous computing. For running Qwen3.6 with KTransformers, see the KTransformers Deployment Guide.

Hugging Face Transformers

Hugging Face Transformers contains a lightweight server which can be used for quick testing and moderate load deployment. The latest transformers is required for Qwen3.6:

shell

pip install "transformers[serving]"

See its documentation for more details. Please also make sure torchvision and pillow are installed.

Then, run transformers serve to launch a server with API endpoints at http://localhost:8000/v1; it will place the model on accelerators if available:

shell

transformers serve Qwen/Qwen3.6-27B --port 8000 --continuous-batching

Using Qwen3.6 via the Chat Completions API

The chat completions API is accessible via standard HTTP requests or OpenAI SDKs. Here, we show examples using the OpenAI Python SDK.

Before starting, make sure it is installed and the API key and the API base URL is configured, e.g.:

shell

pip install -U openai

# Set the following accordingly
export OPENAI_BASE_URL="http://localhost:8000/v1"
export OPENAI_API_KEY="EMPTY"

[!Tip] We recommend using the following set of sampling parameters for generation - Thinking mode for general tasks: temperature=1.0, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0 - Thinking mode for precise coding tasks (e.g. WebDev): temperature=0.6, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0 - Instruct (or non-thinking) mode: temperature=0.7, top_p=0.80, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0 Please note that the support for sampling parameters varies according to inference frameworks.

[!Important] Qwen3.6 models operate in thinking mode by default, generating thinking content signified by <think>\n...</think>\n\n before producing the final responses. To disable thinking content and obtain direct response, refer to the examples here.

Text-Only Input

python

from openai import OpenAI
# Configured by environment variables
client = OpenAI()

messages = [
    {"role": "user", "content": "Type \"I love Qwen3.6\" backwards"},
]

chat_response = client.chat.completions.create(
    model="Qwen/Qwen3.6-27B",
    messages=messages,
    max_tokens=81920,
    temperature=1.0,
    top_p=0.95,
    presence_penalty=0.0,
    extra_body={
        "top_k": 20,
    }, 
)
print("Chat response:", chat_response)

Image Input

python

from openai import OpenAI
# Configured by environment variables
client = OpenAI()

messages = [
    {
        "role": "user",
        "content": [
            {
                "type": "image_url",
                "image_url": {
                    "url": "https://qianwen-res.oss-accelerate.aliyuncs.com/Qwen3.5/demo/CI_Demo/mathv-1327.jpg"
                }
            },
            {
                "type": "text",
                "text": "The centres of the four illustrated circles are in the corners of the square. The two big circles touch each other and also the two little circles. With which factor do you have to multiply the radii of the little circles to obtain the radius of the big circles?\nChoices:\n(A) $\\frac{2}{9}$\n(B) $\\sqrt{5}$\n(C) $0.8 \\cdot \\pi$\n(D) 2.5\n(E) $1+\\sqrt{2}$"
            }
        ]
    }
]

response = client.chat.completions.create(
    model="Qwen/Qwen3.6-27B",
    messages=messages,
    max_tokens=81920,
    temperature=1.0,
    top_p=0.95,
    presence_penalty=0.0,
    extra_body={
        "top_k": 20,
    }, 
)
print("Chat response:", chat_response)

Video Input

python

from openai import OpenAI
# Configured by environment variables
client = OpenAI()

messages = [
    {
        "role": "user",
        "content": [
            {
                "type": "video_url",
                "video_url": {
                    "url": "https://qianwen-res.oss-accelerate.aliyuncs.com/Qwen3.5/demo/video/N1cdUjctpG8.mp4"
                }
            },
            {
                "type": "text",
                "text": "How many porcelain jars were discovered in the niches located in the primary chamber of the tomb?"
            }
        ]
    }
]

# When vLLM is launched with `--media-io-kwargs '{"video": {"num_frames": -1}}'`,
# video frame sampling can be configured via `extra_body` (e.g., by setting `fps`).
# This feature is currently supported only in vLLM.
#
# By default, `fps=2` and `do_sample_frames=True`.
# With `do_sample_frames=True`, you can customize the `fps` value to set your desired video sampling rate.
response = client.chat.completions.create(
    model="Qwen/Qwen3.6-27B",
    messages=messages,
    max_tokens=81920,
    temperature=1.0,
    top_p=0.95,
    presence_penalty=0.0,
    extra_body={
        "top_k": 20,
        "mm_processor_kwargs": {"fps": 2, "do_sample_frames": True},
    }, 
)

print("Chat response:", chat_response)

Instruct (or Non-Thinking) Mode

[!Important] Qwen3.6 does not officially support the soft switch of Qwen3, i.e., /think and /nothink.

Qwen3.6 will think by default before response. You can obtain direct response from the model without thinking by configuring the API parameters. For example,

python

from openai import OpenAI
# Configured by environment variables
client = OpenAI()

messages = [
    {
        "role": "user",
        "content": [
            {
                "type": "image_url",
                "image_url": {
                    "url": "https://qianwen-res.oss-accelerate.aliyuncs.com/Qwen3.6/demo/RealWorld/RealWorld-04.png"
                }
            },
            {
                "type": "text",
                "text": "Where is this?"
            }
        ]
    }
]

chat_response = client.chat.completions.create(
    model="Qwen/Qwen3.6-27B",
    messages=messages,
    max_tokens=32768,
    temperature=0.7,
    top_p=0.8,
    presence_penalty=1.5,
    extra_body={
        "top_k": 20,
        "chat_template_kwargs": {"enable_thinking": False},
    }, 
)
print("Chat response:", chat_response)

[!Note] If you are using APIs from Alibaba Cloud Model Studio, in addition to changing model, please use "enable_thinking": False instead of "chat_template_kwargs": {"enable_thinking": False}.

Preserve Thinking

By default, only the thinking blocks generated in handling the latest user message is retained, resulting in a pattern commonly as interleaved thinking. Qwen3.6 has been additionally trained to preserve and leverage thinking traces from historical messages. You can enable this behavior by setting the preserve_thinking option:

python

from openai import OpenAI
# Configured by environment variables
client = OpenAI()

messages = [...]

chat_response = client.chat.completions.create(
    model="Qwen/Qwen3.6-27B",
    messages=messages,
    max_tokens=32768,
    temperature=0.6,
    top_p=0.95,
    presence_penalty=0.0,
    extra_body={
        "top_k": 20,
        "chat_template_kwargs": {"preserve_thinking": True},
    }, 
)
print("Chat response:", chat_response)

[!Note] If you are using APIs from Alibaba Cloud Model Studio, in addition to changing model, please use "preserve_thinking": True instead of "chat_template_kwargs": {"preserve_thinking": False}.

This capability is particularly beneficial for agent scenarios, where maintaining full reasoning context can enhance decision consistency and, in many cases, reduce overall token consumption by minimizing redundant reasoning. Additionally, it can improve KV cache utilization, optimizing inference efficiency in both thinking and non-thinking modes.

Agentic Usage

Qwen3.6 excels in tool calling capabilities.

Qwen-Agent

We recommend using Qwen-Agent to quickly build Agent applications with Qwen3.6.

To define the available tools, you can use the MCP configuration file, use the integrated tool of Qwen-Agent, or integrate other tools by yourself.

python

import os
from qwen_agent.agents import Assistant

# Define LLM
# Using Alibaba Cloud Model Studio
llm_cfg = {
    # Use the OpenAI-compatible model service provided by DashScope:
    'model': 'qwen3.6-27b',
    'model_type': 'qwenvl_oai',
    'model_server': 'https://dashscope.aliyuncs.com/compatible-mode/v1',
    'api_key': os.getenv('DASHSCOPE_API_KEY'),

    'generate_cfg': {
        'use_raw_api': True,
        # When using Dash Scope OAI API, pass the parameter of whether to enable thinking mode in this way
        'extra_body': {
            'enable_thinking': True,
            'preserve_thinking': True,
        },
    },
}

# Using OpenAI-compatible API endpoint.
# functionality of the deployment frameworks and let Qwen-Agent automate the related operations.
#
# llm_cfg = {
#     # Use your own model service compatible with OpenAI API by vLLM/SGLang:
#     'model': 'Qwen/Qwen3.6-27B',
#     'model_type': 'qwenvl_oai',
#     'model_server': 'http://localhost:8000/v1',  # api_base
#     'api_key': 'EMPTY',
#
#     'generate_cfg': {
#         'use_raw_api': True,
#         # When using vLLM/SGLang OAI API, pass the parameter of whether to enable thinking mode in this way
#         'extra_body': {
#             'chat_template_kwargs': {'enable_thinking': True, 'preserve_thinking': True}
#         },
#     },
# }

# Define Tools
tools = [
    {'mcpServers': {  # You can specify the MCP configuration file
            "filesystem": {
                "command": "npx",
                "args": ["-y", "@modelcontextprotocol/server-filesystem", "/Users/xxxx/Desktop"]
            }
        }
    }
]

# Define Agent
bot = Assistant(llm=llm_cfg, function_list=tools)

# Streaming generation
messages = [{'role': 'user', 'content': 'Help me organize my desktop.'}]
for responses in bot.run(messages=messages):
    pass
print(responses)

# Streaming generation
messages = [{'role': 'user', 'content': 'Develop a dog website and save it on the desktop'}]
for responses in bot.run(messages=messages):
    pass
print(responses)

Qwen Code

Qwen Code is an open-source AI agent for the terminal, optimized for Qwen models. It helps you understand large codebases, automate tedious work, and ship faster.

For more information, please refer to Qwen Code.

Processing Ultra-Long Texts

Qwen3.6 natively supports context lengths of up to 262,144 tokens. For long-horizon tasks where the total length (including both input and output) exceeds this limit, we recommend using RoPE scaling techniques to handle long texts effectively., e.g., YaRN.

YaRN is currently supported by several inference frameworks, e.g., transformers, vllm, ktransformers and sglang. In general, there are two approaches to enabling YaRN for supported frameworks:

—Modifying the model configuration file: In the config.json file, change the rope_parameters fields in text_config to:

json

    {
        "mrope_interleaved": true,
        "mrope_section": [
            11,
            11,
            10
        ],
        "rope_type": "yarn",
        "rope_theta": 10000000,
        "partial_rotary_factor": 0.25,
        "factor": 4.0,
        "original_max_position_embeddings": 262144,
    }

—Passing command line arguments:

For vllm, you can use

shell

    VLLM_ALLOW_LONG_MAX_MODEL_LEN=1 vllm serve ... --hf-overrides '{"text_config": {"rope_parameters": {"mrope_interleaved": true, "mrope_section": [11, 11, 10], "rope_type": "yarn", "rope_theta": 10000000, "partial_rotary_factor": 0.25, "factor": 4.0, "original_max_position_embeddings": 262144}}}' --max-model-len 1010000

For sglang and ktransformers, you can use

shell

    SGLANG_ALLOW_OVERWRITE_LONGER_CONTEXT_LEN=1 python -m sglang.launch_server ... --json-model-override-args '{"text_config": {"rope_parameters": {"mrope_interleaved": true, "mrope_section": [11, 11, 10], "rope_type": "yarn", "rope_theta": 10000000, "partial_rotary_factor": 0.25, "factor": 4.0, "original_max_position_embeddings": 262144}}}' --context-length 1010000

[!NOTE] All the notable open-source frameworks implement static YaRN, which means the scaling factor remains constant regardless of input length, potentially impacting performance on shorter texts. We advise modifying the rope_parameters configuration only when processing long contexts is required. It is also recommended to modify the factor as needed. For example, if the typical context length for your application is 524,288 tokens, it would be better to set factor as 2.0.

Best Practices

To achieve optimal performance, we recommend the following settings:

1.Sampling Parameters:
2.We suggest using the following sets of sampling parameters depending on the mode and task type:
3.Thinking mode for general tasks: temperature=1.0, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0
4.Thinking mode for precise coding tasks (e.g., WebDev): temperature=0.6, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0
5.Instruct (or non-thinking) mode: temperature=0.7, top_p=0.80, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0
6.For supported frameworks, you can adjust the presence_penalty parameter between 0 and 2 to reduce endless repetitions. However, using a higher value may occasionally result in language mixing and a slight decrease in model performance.

1.Adequate Output Length: We recommend using an output length of 32,768 tokens for most queries. For benchmarking on highly complex problems, such as those found in math and programming competitions, we suggest setting the max output length to 81,920 tokens. This provides the model with sufficient space to generate detailed and comprehensive responses, thereby enhancing its overall performance.

1.Standardize Output Format: We recommend using prompts to standardize model outputs when benchmarking.
2.Math Problems: Include "Please reason step by step, and put your final answer within \boxed{}." in the prompt.
3.Multiple-Choice Questions: Add the following JSON structure to the prompt to standardize responses: "Please show your choice in the answer field with only the choice letter, e.g., "answer": "C"."

1.Long Video Understanding: To optimize inference efficiency for plain text and images, the size parameter in the released video_preprocessor_config.json is conservatively configured. It is recommended to set the longest_edge parameter in the videopreprocessorconfig file to 469,762,048 (corresponding to 224k video tokens) to enable higher frame-rate sampling for hour-scale videos and thereby achieve superior performance. For example,

json

    {"longest_edge": 469762048, "shortest_edge": 4096}

Alternatively, override the default values via engine startup parameters. For implementation details, refer to: vLLM / SGLang.

Citation

If you find our work helpful, feel free to give us a cite.

bibtex

@misc{qwen3.6-27b,
    title  = {{Qwen3.6-27B}: Flagship-Level Coding in a {27B} Dense Model},
    author = {{Qwen Team}},
    month  = {April},
    year   = {2026},
    url    = {https://qwen.ai/blog?id=qwen3.6-27b}
}

<h2> EXAMPLE GENERATION(s): </h2>

Some formatting may be lost on copy/paste.

Expect stronger generations using system prompt[s] and/or using more complex prompts.

Temp 1, rep pen 1 [off], topp .95 minp .05 topk 64

TWO EXAMPLE generations below, first one is 13k (!), second is "creative"

EXAMPLE #1

<h2>Sample Generation:</h2>

Q4KS (4-bit) ; non imatrix, standard default settings for Qwen 3.6 version model.

NOTES:

—Some formatting lost on copy/paste ; original is flawless in terms of formatting, tables and charts.
—Q4KS non-imatrix represents LOW end of the quality scale at 1/4 the precision of the full model.
—Export of MTP generated content is broken in LMStudio (all formats)

PROMPT:

Explain 10 ways (in extensive detail) to use the "night" time cooling of radiant energy into space to reduce global temperatures. Include charts, and tables.

Thought for 8.68 seconds The user wants me to explain 10 ways to use nighttime radiative cooling (radiation of energy to space) to reduce global temperatures. This is a fascinating topic combining atmospheric physics, climate engineering, and engineering design. Let me think about what radiative cooling to space means: <ul> <li>At night, especially under clear skies, surfaces can radiate thermal energy directly to space through the "infrared window" (roughly 8-13 μm wavelength range) where the atmosphere is relatively transparent</li> <li>This causes surfaces to cool below ambient air temperature (radiative cooling)</li> <li>This is why we see frost even when air temperatures are above freezing</li> </ul> Now I need to think of 10 extensive approaches to leverage this phenomenon for global temperature reduction: <ol> <li>Radiative cooling materials for buildings and infrastructure - Coatings, tiles, films that maximize emission in the IR window and minimize solar absorption</li> <li>Large-scale radiative cooling panels/farms - Dedicated areas of optimized radiative surfaces</li> <li>Nighttime ocean radiative cooling enhancement - Artificial surfaces or materials in oceans to radiate heat at night</li> <li>Atmospheric water harvesting through radiative cooling - Condensing moisture which has cooling effects and water benefits</li> <li>Radiative cooling towers - Structures similar to cooling towers but using radiative cooling to chill water for district cooling or direct injection</li> <li>Selective surface radiators in the upper atmosphere - Balloons or structures at high altitude where radiative cooling is more effective</li> <li>Enhanced desert radiative cooling - Modifying desert surfaces to maximize nighttime heat loss</li> <li>Radiative cooling combined with heat pumps - Using radiative cooling as heat sink for heat pumps at night</li> <li>Nighttime urban radiative cooling corridors - Designing urban areas to channel and enhance radiative cooling effects</li> <li>Radiative cooling for carbon capture enhancement - Using radiative cooling surfaces to condense CO2 or enhance carbon capture systems</li> </ol> I'll develop these concepts with detailed scientific analysis, supporting visual representations, and practical implementation strategies for each approach.

OUTPUT: <h1 class="western" style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Radiative Nighttime Cooling for Global Temperature Reduction: Ten Comprehensive Approaches</h1> <h2 class="western" style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Introduction to Radiative Cooling to Space</h2> Radiative cooling occurs when a surface emits thermal radiation to the cold sky, particularly through the atmospheric "infrared window" (8–13 μm) where greenhouse gases are relatively transparent. At night, under clear conditions, surfaces can lose more energy than they gain, cooling below ambient air temperature—sometimes by 10–15°C or more. This natural phenomenon, responsible for nighttime frost, can be engineered into systematic climate intervention strategies. This document examines ten approaches to harness this effect at scale for global temperature mitigation. <hr/>

<h2 class="western" style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> 1. Radiative Cooling Building Envelopes and Infrastructure</h2> <h3 class="western" style="border: none; padding: 0cm">Principle and Physics</h3> Buildings and paved surfaces constitute ~40% of the urban surface area globally. Replacing conventional materials with selective radiative cooling coatings that maximize emission in the 8–13 μm atmospheric window while minimizing solar absorption can transform urban areas from heat sources to heat sinks. The net radiative heat flux from a surface is: Qnet = εsurface · σ · Tsurface⁴ - Qsolar(1-α) - QdownwardIR - Qconvective - Qconductive Where: <ul> <li>εsurface = emissivity of surface in IR window</li> <li>σ = Stefan-Boltzmann constant (5.67×10⁻⁸ W/m²/K⁴)</li> <li>α = solar reflectivity</li> <li>QdownwardIR = atmospheric downwelling IR radiation</li> <li>Qconvective/conductive = sensible heat transfer to/from surroundings</li> </ul> <h3 class="western" style="border: none; padding: 0cm">Materials and Engineering</h3> Optimal coating properties: <ul> <li>Emissivity >0.90 in 8–13 μm band</li> <li>Solar reflectivity >0.85</li> <li>Durability: >20 years outdoor exposure</li> <li>Cost: <$5/m² at scale</li> </ul> Current material classes: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Material Class </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> IR Emissivity (8-13μm) </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Solar Reflectivity </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Nighttime ΔT (°C) </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Cost ($/m²) </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">High-performance polymer coatings </td> <td style="border: none; padding: 0cm">0.92 </td> <td style="border: none; padding: 0cm">0.88 </td> <td style="border: none; padding: 0cm">-14 </td> <td style="border: none; padding: 0cm">8-15 </td> </tr> <tr> <td style="border: none; padding: 0cm">Spectrally selective paints (SiO₂/MgO) </td> <td style="border: none; padding: 0cm">0.88 </td> <td style="border: none; padding: 0cm">0.82 </td> <td style="border: none; padding: 0cm">-10 </td> <td style="border: none; padding: 0cm">3-6 </td> </tr> <tr> <td style="border: none; padding: 0cm">Metamaterial photonic coolers </td> <td style="border: none; padding: 0cm">0.95 </td> <td style="border: none; padding: 0cm">0.91 </td> <td style="border: none; padding: 0cm">-17 </td> <td style="border: none; padding: 0cm">50+ </td> </tr> <tr> <td style="border: none; padding: 0cm">Bare concrete (control) </td> <td style="border: none; padding: 0cm">0.85 </td> <td style="border: none; padding: 0cm">0.40 </td> <td style="border: none; padding: 0cm">-4 </td> <td style="border: none; padding: 0cm">2 </td> </tr> <tr> <td style="border: none; padding: 0cm">Bitumen asphalt (control) </td> <td style="border: none; padding: 0cm">0.90 </td> <td style="border: none; padding: 0cm">0.08 </td> <td style="border: none; padding: 0cm">+2 </td> <td style="border: none; padding: 0cm">3 </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Implementation Scale</h3> Global urban area breakdown: <ul> <li>Roofs: ~100 million km²</li> <li>Walls: ~150 million km²</li> <li>Pavements: ~180 million km²</li> <li>Total addressable: ~430 million km²</li> </ul> Phase 1 (2025-2035): 10% coverage (43 million km²) <ul> <li>Focus: New construction mandates, retrofit high-value infrastructure</li> <li>Investment: $200-400 billion</li> </ul> Phase 2 (2035-2050): 30% coverage (129 million km²) <ul> <li>Include: Residential retrofitting programs, public infrastructure</li> <li>Cumulative investment: $1-1.5 trillion</li> </ul> Phase 3 (2050-2075): 50-70% coverage <ul> <li>Global standard building codes</li> <li>Cumulative investment: $2-3 trillion</li> </ul> <h3 class="western" style="border: none; padding: 0cm">Cooling Performance</h3> Nighttime radiative cooling power by latitude: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Latitude Band </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Clear Sky Nights/Year </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Avg Radiative Power (W/m²) </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Max ΔT vs Ambient (°C) </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">0-20° (Tropical) </td> <td style="border: none; padding: 0cm">180-250 </td> <td style="border: none; padding: 0cm">45-65 </td> <td style="border: none; padding: 0cm">-8 to -12 </td> </tr> <tr> <td style="border: none; padding: 0cm">20-40° (Subtropical) </td> <td style="border: none; padding: 0cm">200-280 </td> <td style="border: none; padding: 0cm">55-80 </td> <td style="border: none; padding: 0cm">-12 to -16 </td> </tr> <tr> <td style="border: none; padding: 0cm">40-60° (Temperate) </td> <td style="border: none; padding: 0cm">150-220 </td> <td style="border: none; padding: 0cm">60-90 </td> <td style="border: none; padding: 0cm">-10 to -14 </td> </tr> <tr> <td style="border: none; padding: 0cm">60-90° (Boreal) </td> <td style="border: none; padding: 0cm">100-180 </td> <td style="border: none; padding: 0cm">40-70 </td> <td style="border: none; padding: 0cm">-6 to -10 </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Global Impact Estimate</h3> Assuming 40% global urban coverage with advanced radiative cooling materials: <ul> <li>Average nighttime cooling power: 50 W/m² effective</li> <li>Area: 172 million km² = 1.72×10¹⁴ m²</li> <li>Night hours/year: ~4,380 hours = 1.58×10⁷ s</li> <li>Total annual energy diverted: 50 × 1.72×10¹⁴ × 1.58×10⁷ = 1.36×10²³ J = 136 exajoules/year</li> </ul> Equivalent to removing ~500 million metric tons CO₂ equivalent per year <h3 class="western" style="border: none; padding: 0cm">Challenges</h3> <ol> <li>Humidity/fog reduces IR transmission through atmospheric window</li> <li>Wind increases convective heat transfer, offsetting radiative cooling</li> <li>Long-term material durability and maintenance</li> <li>Requires policy mandates for new construction and retrofits</li> </ol> <hr/>

<h2 class="western" style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> 2. Dedicated Radiative Cooling Farms</h2> <h3 class="western" style="border: none; padding: 0cm">Concept</h3> Purpose-built facilities consisting of large, optimized radiative cooling surfaces designed explicitly for climate cooling rather than as building byproducts. These "cooling farms" would be situated in arid or semi-arid regions where nighttime clear skies are prevalent. <h3 class="western" style="border: none; padding: 0cm">System Design</h3> Component layout: <ul> <li>Radiative panels: 80% of surface area</li> <li>Support structures: 10%</li> <li>Monitoring and control: 5%</li> <li>Access and infrastructure: 5%</li> </ul> Panel specifications: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Parameter </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Specification </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Panel dimensions </td> <td style="border: none; padding: 0cm">10 m × 5 m (50 m² each) </td> </tr> <tr> <td style="border: none; padding: 0cm">Tilt angle </td> <td style="border: none; padding: 0cm">0-45° (optimizable by latitude) </td> </tr> <tr> <td style="border: none; padding: 0cm">Surface material </td> <td style="border: none; padding: 0cm">SiO₂/MgO composite coating on aluminum substrate </td> </tr> <tr> <td style="border: none; padding: 0cm">Spacing </td> <td style="border: none; padding: 0cm">2 m minimum (air circulation) </td> </tr> <tr> <td style="border: none; padding: 0cm">Thermal mass </td> <td style="border: none; padding: 0cm">Minimized (rapid nightly cooling) </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Heat Transfer Mechanisms</h3> Three primary pathways for heat removal: <ol> <li>Direct radiative loss to space (primary, 60-70%)</li> <li>Convective transfer to night air, then vertical mixing (20-30%)</li> <li>Conductive transfer to ground (variable, minimized)</li> </ol> Radiative heat loss calculation (typical clear night): Surface temperature: 278 K (5°C) Surface emissivity in window: 0.92 Effective sky temperature (clear desert night): 258 K (-15°C) Qrad = ε · σ · (Tsurface⁴ - Tsky⁴) Qrad = 0.92 × 5.67×10⁻⁸ × (278⁴ - 258⁴) Q_rad ≈ 78 W/m² <h3 class="western" style="border: none; padding: 0cm">Site Selection Criteria</h3> Optimal characteristics: <ul> <li>Low humidity (<40% RH at night)</li> <li>High nighttime cloud cover probability (>70%)</li> <li>Low wind speed at night (<5 m/s average)</li> <li>Flat terrain</li> <li>Non-agricultural land</li> <li>Access to monitoring infrastructure</li> </ul> Global candidate regions: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Region </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Area Available (km²) </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Annual Clear Night Hours </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Avg Cooling Power (W/m²) </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Sahara Desert </td> <td style="border: none; padding: 0cm">500,000 </td> <td style="border: none; padding: 0cm">2,800 </td> <td style="border: none; padding: 0cm">65 </td> </tr> <tr> <td style="border: none; padding: 0cm">Arabian Desert </td> <td style="border: none; padding: 0cm">150,000 </td> <td style="border: none; padding: 0cm">2,600 </td> <td style="border: none; padding: 0cm">60 </td> </tr> <tr> <td style="border: none; padding: 0cm">Australian Outback </td> <td style="border: none; padding: 0cm">400,000 </td> <td style="border: none; padding: 0cm">2,400 </td> <td style="border: none; padding: 0cm">55 </td> </tr> <tr> <td style="border: none; padding: 0cm">Gobi Desert </td> <td style="border: none; padding: 0cm">80,000 </td> <td style="border: none; padding: 0cm">2,200 </td> <td style="border: none; padding: 0cm">50 </td> </tr> <tr> <td style="border: none; padding: 0cm">Great Basin (USA) </td> <td style="border: none; padding: 0cm">30,000 </td> <td style="border: none; padding: 0cm">2,000 </td> <td style="border: none; padding: 0cm">45 </td> </tr> <tr> <td style="border: none; padding: 0cm">Patagonia </td> <td style="border: none; padding: 0cm">50,000 </td> <td style="border: none; padding: 0cm">1,800 </td> <td style="border: none; padding: 0cm">40 </td> </tr> <tr> <td style="border: none; padding: 0cm">Total </td> <td style="border: none; padding: 0cm">1,240,000 </td> <td style="border: none; padding: 0cm">~2,200 </td> <td style="border: none; padding: 0cm">~55 </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Scale and Economics</h3> Single facility (100 km²): <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Metric </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Value </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Radiative panel area </td> <td style="border: none; padding: 0cm">80 km² = 8×10⁷ m² </td> </tr> <tr> <td style="border: none; padding: 0cm">Avg nighttime cooling power </td> <td style="border: none; padding: 0cm">50 W/m² </td> </tr> <tr> <td style="border: none; padding: 0cm">Annual heat diverted </td> <td style="border: none; padding: 0cm">8.8×10¹⁶ J/year (88 PJ) </td> </tr> <tr> <td style="border: none; padding: 0cm">Initial capital cost </td> <td style="border: none; padding: 0cm">$400 million </td> </tr> <tr> <td style="border: none; padding: 0cm">O&M annual cost </td> <td style="border: none; padding: 0cm">$4 million </td> </tr> <tr> <td style="border: none; padding: 0cm">Cost per ton CO₂eq </td> <td style="border: none; padding: 0cm">$5-10/ton-year </td> </tr> </tbody> </table> Global deployment scenario: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Phase </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Facilities </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Total Area (km²) </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Annual Heat Diverted (EJ) </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Cumulative Cost (B$) </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">1 (pilot) </td> <td style="border: none; padding: 0cm">10 </td> <td style="border: none; padding: 0cm">1,000 </td> <td style="border: none; padding: 0cm">8.8 </td> <td style="border: none; padding: 0cm">5 </td> </tr> <tr> <td style="border: none; padding: 0cm">2 (scale) </td> <td style="border: none; padding: 0cm">100 </td> <td style="border: none; padding: 0cm">10,000 </td> <td style="border: none; padding: 0cm">88 </td> <td style="border: none; padding: 0cm">50 </td> </tr> <tr> <td style="border: none; padding: 0cm">3 (regional) </td> <td style="border: none; padding: 0cm">500 </td> <td style="border: none; padding: 0cm">50,000 </td> <td style="border: none; padding: 0cm">440 </td> <td style="border: none; padding: 0cm">250 </td> </tr> <tr> <td style="border: none; padding: 0cm">4 (global) </td> <td style="border: none; padding: 0cm">2,000 </td> <td style="border: none; padding: 0cm">200,000 </td> <td style="border: none; padding: 0cm">1,760 </td> <td style="border: none; padding: 0cm">1,000 </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Climate Impact</h3> At Phase 4 deployment (200,000 km²): <ul> <li>Annual heat diverted: 1,760 EJ</li> <li>CO₂ equivalent: ~7,000 metric tons/year</li> <li>Estimated global temperature effect: 0.01-0.03°C</li> </ul> While modest alone, radiative cooling farms provide: <ul> <li>Zero operational emissions</li> <li>Potential co-production of water (condensation)</li> <li>Synergistic use with solar PV (daytime solar, nighttime cooling)</li> <li>Demonstrable, measurable effects for monitoring</li> </ul> <hr/>

<code class="western">Heat Gains:</code> <code class="western">├── </code><code class="western">Downwelling IR from atmosphere 30-50 W/m²</code> <code class="western">├── </code><code class="western">Heat from subsurface mixing 10-30 W/m²</code> <code class="western">└── </code><code class="western">Upwelling from depth variable</code></pre> Net: Often slightly positive (ocean gains heat) due to mixing and evaporation With enhancement (microlayer approach): <pre class="western" style="border: none; padding: 0cm"><code class="western">Modified budget:</code> <code class="western">├── </code><code class="western">Radiative loss to space (enhanced) 60-80 W/m² (+20-30%)</code> <code class="western">├── </code><code class="western">Evaporative loss (reduced) 5-15 W/m² (-60-70%)</code> <code class="western">├── </code><code class="western">Convective loss 5-10 W/m²</code> <code class="western">├── </code><code class="western">Downwelling IR (unchanged) 30-50 W/m²</code> <code class="western">└── </code><code class="western">Heat from mixing (reduced) 2-8 W/m² (-70-80%)</code></pre> Net: 15-35 W/m² heat LOSS to atmosphere/space <h3 class="western" style="border: none; padding: 0cm">Implementation Infrastructure</h3> Microlayer deployment system: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Component </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Description </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Carrier vessels </td> <td style="border: none; padding: 0cm">Modified tankers, autonomous surface vehicles </td> </tr> <tr> <td style="border: none; padding: 0cm">Distribution </td> <td style="border: none; padding: 0cm">Boom spreaders, spray systems </td> </tr> <tr> <td style="border: none; padding: 0cm">Target areas </td> <td style="border: none; padding: 0cm">5-15 km² patches </td> </tr> <tr> <td style="border: none; padding: 0cm">Frequency </td> <td style="border: none; padding: 0cm">Daily (material biodegrades) </td> </tr> <tr> <td style="border: none; padding: 0cm">Cost </td> <td style="border: none; padding: 0cm">$50-200 per km² per day </td> </tr> </tbody> </table> Seasonal deployment strategy: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Region </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Active Months </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Rationale </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Arctic </td> <td style="border: none; padding: 0cm">May-September </td> <td style="border: none; padding: 0cm">Maximum daylight/heat gain period </td> </tr> <tr> <td style="border: none; padding: 0cm">Subarctic (N) </td> <td style="border: none; padding: 0cm">June-September </td> <td style="border: none; padding: 0cm">Peak warming </td> </tr> <tr> <td style="border: none; padding: 0cm">Subarctic (S) </td> <td style="border: none; padding: 0cm">December-March </td> <td style="border: none; padding: 0cm">Peak warming </td> </tr> <tr> <td style="border: none; padding: 0cm">Tropical Pacific </td> <td style="border: none; padding: 0cm">Year-round </td> <td style="border: none; padding: 0cm">Consistent conditions </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Global Potential</h3> Assuming 1% of ocean surface treated (3.6 million km²): <ul> <li>Average nighttime cooling power: 20 W/m² net</li> <li>Night hours/year: 4,380 hours</li> <li>Annual heat removed: 20 × 3.6×10¹² × 1.58×10⁷ = 1.14×10²¹ J = 1,140 EJ/year</li> </ul> CO₂ equivalent removal: ~4,500 metric tons/year <h3 class="western" style="border: none; padding: 0cm">Risks and Considerations</h3> <ol> <li>Ecosystem impact: Potential effects on marine organisms, especially plankton and larval stages</li> <li>Material accumulation: Risk of microplastic pollution if biodegradation fails</li> <li>Altered evaporation: Changes to precipitation patterns</li> <li>Economic viability: High ongoing costs for material production and deployment</li> <li>Regulatory complexity: International waters governance</li> </ol> <hr/>

<h2 class="western" style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> 5. Radiative Cooling Towers</h2> <h3 class="western" style="border: none; padding: 0cm">Concept</h3> Massive structures analogous to industrial cooling towers, but designed to radiate heat directly to space rather than using evaporative cooling. These towers maximize surface area-to-volume ratio for radiative loss and are positioned to access cooler nighttime air. <h3 class="western" style="border: none; padding: 0cm">Engineering Design</h3> Tower geometry: <ul> <li>Hyperboloid shape (similar to existing cooling towers)</li> <li>Height: 100-300 m</li> <li>Base diameter: 150-400 m</li> <li>Top diameter: 50-150 m</li> </ul> Surface treatment: <ul> <li>Entire interior and exterior coated with high-emissivity, high-solar-reflectivity materials</li> <li>Surface area per tower: 50,000-300,000 m²</li> </ul> Heat transfer modes within tower: <ol> <li>Air-borne heat removal (natural convection): <ul> <li>Warm air rises through tower, cooling via contact with radiating walls</li> <li>Heat radiated from walls to night sky</li> <li>Cooled air exits at top and disperses</li> </ul> <li>Liquid-borne heat removal (optional): <ul> <li>Warm water circulated through tower exterior/interior</li> <li>Water cooled radiatively, then pumped back to source</li> <li>Can serve district cooling applications</li> </ul> </ol> <h3 class="western" style="border: none; padding: 0cm">Performance Calculations</h3> Radiative cooling tower (200 m tall, 200 m base diameter): <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Parameter </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Value </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Surface area </td> <td style="border: none; padding: 0cm">180,000 m² </td> </tr> <tr> <td style="border: none; padding: 0cm">Effective emissivity </td> <td style="border: none; padding: 0cm">0.88 </td> </tr> <tr> <td style="border: none; padding: 0cm">Average night temperature </td> <td style="border: none; padding: 0cm">15°C </td> </tr> <tr> <td style="border: none; padding: 0cm">Effective sky temperature (clear) </td> <td style="border: none; padding: 0cm">-10°C </td> </tr> <tr> <td style="border: none; padding: 0cm">Radiative power per m² </td> <td style="border: none; padding: 0cm">~55 W/m² </td> </tr> <tr> <td style="border: none; padding: 0cm">Total radiative cooling power </td> <td style="border: none; padding: 0cm">9.9 MW </td> </tr> <tr> <td style="border: none; padding: 0cm">Annual heat removed (clear nights) </td> <td style="border: none; padding: 0cm">1.2×10¹¹ kJ </td> </tr> </tbody> </table> Comparison to conventional evaporative tower: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Metric </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Radiative Tower </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Evaporative Tower </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Cooling capacity </td> <td style="border: none; padding: 0cm">10-20 MW </td> <td style="border: none; padding: 0cm">50-100 MW </td> </tr> <tr> <td style="border: none; padding: 0cm">Water usage </td> <td style="border: none; padding: 0cm">0 L/h </td> <td style="border: none; padding: 0cm">5,000-10,000 L/h </td> </tr> <tr> <td style="border: none; padding: 0cm">Energy input </td> <td style="border: none; padding: 0cm">0-50 kW </td> <td style="border: none; padding: 0cm">500 kW-2 MW </td> </tr> <tr> <td style="border: none; padding: 0cm">Nighttime efficiency </td> <td style="border: none; padding: 0cm">100% (passive) </td> <td style="border: none; padding: 0cm">70-90% </td> </tr> <tr> <td style="border: none; padding: 0cm">Climate benefit </td> <td style="border: none; padding: 0cm">Direct + no emissions </td> <td style="border: none; padding: 0cm">Direct only </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Heat Sink Applications</h3> Three primary use cases: <h4 class="western" style="border: none; padding: 0cm">A. Nighttime Urban Heat Disposal</h4> <ul> <li>Collect heat from urban buildings during day (via district heating/thermal storage)</li> <li>Radiate it away at night through cooling towers</li> <li>Reduces daytime air conditioning demand</li> </ul> <h4 class="western" style="border: none; padding: 0cm">B. Power Plant Heat Sink</h4> <ul> <li>Replace or supplement evaporative cooling at thermal/nuclear plants</li> <li>Particularly valuable in water-scarce regions</li> </ul> <h4 class="western" style="border: none; padding: 0cm">C. Direct Climate Cooling</h4> <ul> <li>Towers designed solely to radiate ambient heat to space</li> <li>Positioned in high-altitude, clear-sky regions</li> </ul> <h3 class="western" style="border: none; padding: 0cm">Global Deployment Scenario</h3> Phase 1: 100 radiative cooling towers <ul> <li>Locations: Major urban centers (2-5 per city)</li> <li>Total annual heat removed: 1.2×10¹³ kJ</li> </ul> Phase 2: 1,000 towers <ul> <li>Expanded urban and industrial coverage</li> <li>Total annual heat removed: 1.2×10¹⁴ kJ</li> </ul> Phase 3: 5,000 towers <ul> <li>Global coverage of major population/industrial centers</li> <li>Total annual heat removed: 6×10¹⁴ kJ (0.6 EJ)</li> </ul> Cost estimates: <ul> <li>Construction per tower: $50-200 million</li> <li>Phase 3 total construction: $250-1,000 billion</li> </ul> CO₂ equivalent removal (Phase 3): ~2,500 metric tons/year <h3 class="western" style="border: none; padding: 0cm">Technical Challenges</h3> <ol> <li>Lower cooling capacity than evaporative towers (must overcome with scale)</li> <li>High construction cost per unit</li> <li>Requires clear-sky regions for optimal performance</li> <li>Wind loads and structural design at large heights</li> </ol> <hr/>

<h2 class="western" style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> 6. Upper-Altitude Radiative Cooling Platforms</h2> <h3 class="western" style="border: none; padding: 0cm">Principle</h3> At high altitudes, the atmospheric density is lower, providing less obstruction to radiative cooling. Platforms (balloons, gliders, or satellites) carrying radiative cooling surfaces at 20-50 km altitude can radiate heat directly to space with minimal atmospheric interference. <h3 class="western" style="border: none; padding: 0cm">Platform Types</h3> <h4 class="western" style="border: none; padding: 0cm">A. High-Altitude Balloons</h4> Characteristics: <ul> <li>Operating altitude: 20-35 km</li> <li>Duration: Weeks to months</li> <li>Radiative surface area per balloon: 50-500 m²</li> <li>Power: Solar PV for station-keeping and telemetry</li> </ul> Advantages: <ul> <li>Low cost compared to satellites</li> <li>Easy to deploy and replace</li> <li>Access to mesosphere where IR window is nearly fully open</li> </ul> <h4 class="western" style="border: none; padding: 0cm">B. Aerostats (Buoyant Platforms)</h4> Characteristics: <ul> <li>Operating altitude: 15-30 km</li> <li>Duration: Years</li> <li>Radiative surface area per platform: 500-5,000 m²</li> <li>Power: Solar + batteries</li> </ul> <h4 class="western" style="border: none; padding: 0cm">C. Low-Earth Orbit Satellites</h4> Characteristics: <ul> <li>Altitude: 200-800 km</li> <li>Radiative surface area per satellite: 1,000-10,000 m²</li> <li>No atmospheric obstruction</li> <li>Continuous radiative cooling (except during eclipse)</li> </ul> <h3 class="western" style="border: none; padding: 0cm">Radiative Cooling Performance vs. Altitude</h3> Effective radiative cooling power: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Altitude </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Atmospheric Pressure </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Clear-Sky Factor </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Effective T_sky (K) </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Radiative Power (W/m²) </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">0 km (surface) </td> <td style="border: none; padding: 0cm">1013 mbar </td> <td style="border: none; padding: 0cm">0.70 </td> <td style="border: none; padding: 0cm">248 </td> <td style="border: none; padding: 0cm">45 </td> </tr> <tr> <td style="border: none; padding: 0cm">10 km </td> <td style="border: none; padding: 0cm">265 mbar </td> <td style="border: none; padding: 0cm">0.92 </td> <td style="border: none; padding: 0cm">215 </td> <td style="border: none; padding: 0cm">75 </td> </tr> <tr> <td style="border: none; padding: 0cm">20 km </td> <td style="border: none; padding: 0cm">55 mbar </td> <td style="border: none; padding: 0cm">0.98 </td> <td style="border: none; padding: 0cm">185 </td> <td style="border: none; padding: 0cm">95 </td> </tr> <tr> <td style="border: none; padding: 0cm">35 km </td> <td style="border: none; padding: 0cm">12 mbar </td> <td style="border: none; padding: 0cm">1.00 </td> <td style="border: none; padding: 0cm">165 </td> <td style="border: none; padding: 0cm">110 </td> </tr> <tr> <td style="border: none; padding: 0cm">50+ km (space) </td> <td style="border: none; padding: 0cm">~0 mbar </td> <td style="border: none; padding: 0cm">1.00 </td> <td style="border: none; padding: 0cm">4.2 K </td> <td style="border: none; padding: 0cm">350+ </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">System Design: High-Altitude Balloon Fleet</h3> Single balloon system: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Parameter </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Specification </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Balloon type </td> <td style="border: none; padding: 0cm">Superpressure helium </td> </tr> <tr> <td style="border: none; padding: 0cm">Operating altitude </td> <td style="border: none; padding: 0cm">30 km </td> </tr> <tr> <td style="border: none; padding: 0cm">Radiative surface </td> <td style="border: none; padding: 0cm">200 m² of photonic metamaterial </td> </tr> <tr> <td style="border: none; padding: 0cm">Radiative power </td> <td style="border: none; padding: 0cm">110 W/m² × 200 = 22 kW </td> </tr> <tr> <td style="border: none; padding: 0cm">Lifetime </td> <td style="border: none; padding: 0cm">90 days </td> </tr> <tr> <td style="border: none; padding: 0cm">Cost (including deployment) </td> <td style="border: none; padding: 0cm">$500,000 </td> </tr> </tbody> </table> Fleet of 10,000 balloons (rotated continuously): <ul> <li>Active at any time: ~5,000</li> <li>Total radiative power: 5,000 × 22 kW = 110 MW</li> <li>Annual heat radiated: 110 MW × 3.15×10⁷ s = 3.47×10¹⁵ J = 3,470 GJ</li> <li>Annual operational cost (replacements, telemetry): $2.5 billion</li> </ul> <h3 class="western" style="border: none; padding: 0cm">Satellite-Based System</h3> Constellation design: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Parameter </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Specification </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Number of satellites </td> <td style="border: none; padding: 0cm">500 </td> </tr> <tr> <td style="border: none; padding: 0cm">Orbit </td> <td style="border: none; padding: 0cm">600 km, sun-synchronous </td> </tr> <tr> <td style="border: none; padding: 0cm">Radiative surface per sat </td> <td style="border: none; padding: 0cm">2,000 m² deployable </td> </tr> <tr> <td style="border: none; padding: 0cm">Radiative power per sat </td> <td style="border: none; padding: 0cm">350 W/m² × 2,000 = 700 kW </td> </tr> <tr> <td style="border: none; padding: 0cm">Constellation power </td> <td style="border: none; padding: 0cm">350 MW </td> </tr> <tr> <td style="border: none; padding: 0cm">Lifetime </td> <td style="border: none; padding: 0cm">15 years </td> </tr> <tr> <td style="border: none; padding: 0cm">Cost per satellite </td> <td style="border: none; padding: 0cm">$100 million </td> </tr> <tr> <td style="border: none; padding: 0cm">Total constellation cost </td> <td style="border: none; padding: 0cm">$50 billion </td> </tr> </tbody> </table> Annual heat radiated: 350 MW × 3.15×10⁷ s = 1.10×10¹⁶ J = 11 PJ/year <h3 class="western" style="border: none; padding: 0cm">Cost-Effectiveness Comparison</h3> <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Platform </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Cost per TJ Radiated </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Operational Lifetime </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Notes </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Surface radiative cooler </td> <td style="border: none; padding: 0cm">$0.10 </td> <td style="border: none; padding: 0cm">20+ years </td> <td style="border: none; padding: 0cm">Lowest cost </td> </tr> <tr> <td style="border: none; padding: 0cm">Cooling tower </td> <td style="border: none; padding: 0cm">$0.50 </td> <td style="border: none; padding: 0cm">50+ years </td> <td style="border: none; padding: 0cm">Large-scale </td> </tr> <tr> <td style="border: none; padding: 0cm">High-altitude balloon </td> <td style="border: none; padding: 0cm">$8.00 </td> <td style="border: none; padding: 0cm">90 days </td> <td style="border: none; padding: 0cm">Moderate </td> </tr> <tr> <td style="border: none; padding: 0cm">Aerostat </td> <td style="border: none; padding: 0cm">$5.00 </td> <td style="border: none; padding: 0cm">5-10 years </td> <td style="border: none; padding: 0cm">Medium </td> </tr> <tr> <td style="border: none; padding: 0cm">LEO satellite </td> <td style="border: none; padding: 0cm">$4.50 </td> <td style="border: none; padding: 0cm">15 years </td> <td style="border: none; padding: 0cm">Highest power </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Strategic Value</h3> <ol> <li>High-power radiative cooling: Space-based platforms can radiate 5-10× more per m² than surface systems</li> <li>Geographic flexibility: Can target specific latitudes/longitudes</li> <li>No land use: Eliminates terrestrial ecological concerns</li> <li>Dual-use potential: Platforms could also monitor climate or provide communications</li> <li>Scalable: Start small, expand incrementally</li> </ol> <h3 class="western" style="border: none; padding: 0cm">Challenges</h3> <ol> <li>High cost per unit</li> <li>Space debris and orbital congestion concerns</li> <li>Complex launch and maintenance infrastructure</li> <li>Political/regulatory complexity for space-based climate engineering</li> <li>Single-point failure risk for satellites</li> </ol> <hr/>

<h2 class="western" style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> 8. Radiative Cooling as Heat Sink for Heat Pumps</h2> <h3 class="western" style="border: none; padding: 0cm">Principle</h3> Radiative cooling surfaces can serve as the "cold side" (heat sink) for heat pumps, enabling heat to be pumped from warm sources (buildings, industrial processes, or the atmosphere) to the cold night sky. This amplifies the natural radiative cooling effect through active thermodynamic work. <h3 class="western" style="border: none; padding: 0cm">System Architecture</h3> Nighttime heat pump cycle: <pre class="western" style="border: none; padding: 0cm"><code class="western"> </code><code class="western">[Heat Pump System]</code> <code class="western"> ┌──────────────┐</code> <code class="western"> </code><code class="western">Warm Source (Twarm)│ │ Radiative Cooler (Tcold)</code> <code class="western"> </code><code class="western">(e.g., │ Heat │ ──────► Night Sky (Tsky)</code> <code class="western"> </code><code class="western">building, │ Pump │ (radiative loss)</code> <code class="western"> </code><code class="western">process, │ (COP) │</code> <code class="western"> </code><code class="western">air) │ │</code> <code class="western"> └──────────────┘</code> <code class="western"> ▲</code> <code class="western"> │</code> <code class="western"> </code><code class="western">Electrical Power</code></pre> Key performance metric: Coefficient of Performance (COP) COP = Qcooling / Welectrical Where: <ul> <li>Qcooling = heat removed from warm source</li> <li>W_electrical = electrical power consumed</li> </ul> <h3 class="western" style="border: none; padding: 0cm">Technical Specifications</h3> Heat pump coupled with radiative cooler: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Parameter </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Value </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Warm source temperature </td> <td style="border: none; padding: 0cm">20-30°C </td> </tr> <tr> <td style="border: none; padding: 0cm">Radiative cooler temperature (night) </td> <td style="border: none; padding: 0cm">-5 to 10°C </td> </tr> <tr> <td style="border: none; padding: 0cm">Temperature lift (ΔT) </td> <td style="border: none; padding: 0cm">25-35 K </td> </tr> <tr> <td style="border: none; padding: 0cm">Heat pump type </td> <td style="border: none; padding: 0cm">Scroll or screw compressor </td> </tr> <tr> <td style="border: none; padding: 0cm">COP (at design point) </td> <td style="border: none; padding: 0cm">2.5-4.0 </td> </tr> <tr> <td style="border: none; padding: 0cm">Heat pump capacity </td> <td style="border: none; padding: 0cm">100 kW - 5 MW </td> </tr> <tr> <td style="border: none; padding: 0cm">Annual operating hours </td> <td style="border: none; padding: 0cm">1,500-2,500 </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Cooling Power Amplification</h3> Example: 1 MW heat pump coupled to 50,000 m² radiative cooler: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Parameter </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Calculation </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Result </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Radiative cooler area </td> <td style="border: none; padding: 0cm">- </td> <td style="border: none; padding: 0cm">50,000 m² </td> </tr> <tr> <td style="border: none; padding: 0cm">Radiative power density </td> <td style="border: none; padding: 0cm">60 W/m² </td> <td style="border: none; padding: 0cm">- </td> </tr> <tr> <td style="border: none; padding: 0cm">Passive radiative cooling </td> <td style="border: none; padding: 0cm">50,000 × 60 </td> <td style="border: none; padding: 0cm">3 MW </td> </tr> <tr> <td style="border: none; padding: 0cm">Heat pump capacity </td> <td style="border: none; padding: 0cm">1 MW (electrical input) </td> <td style="border: none; padding: 0cm">- </td> </tr> <tr> <td style="border: none; padding: 0cm">COP </td> <td style="border: none; padding: 0cm">3.0 </td> <td style="border: none; padding: 0cm">- </td> </tr> <tr> <td style="border: none; padding: 0cm">Active heat pumping </td> <td style="border: none; padding: 0cm">1 × 3.0 </td> <td style="border: none; padding: 0cm">3 MW </td> </tr> <tr> <td style="border: none; padding: 0cm">Total heat radiated </td> <td style="border: none; padding: 0cm">3 + 3 </td> <td style="border: none; padding: 0cm">6 MW </td> </tr> </tbody> </table> Result: 2× amplification over passive radiative cooling alone <h3 class="western" style="border: none; padding: 0cm">Applications</h3> <h4 class="western" style="border: none; padding: 0cm">A. District Cooling Systems</h4> <ul> <li>Collect heat from buildings during daytime</li> <li>Store thermally (in water tanks, phase-change materials)</li> <li>Radiate away at night via heat pump + radiative cooler system</li> <li>Reduces or eliminates need for vapor-compression chillers</li> </ul> Annual savings estimate (single urban district): <ul> <li>Replaces 5,000 tons of vapor-compression cooling</li> <li>Eliminates 20 GWh/year electrical consumption</li> <li>Reduces CO₂ emissions: ~10,000 metric tons/year</li> </ul> <h4 class="western" style="border: none; padding: 0cm">B. Industrial Process Cooling</h4> <ul> <li>Industries with nighttime-dominant cooling needs</li> <li>Chemical processing, food processing, pharmaceuticals</li> <li>Potential 30-50% reduction in cooling costs vs. conventional chillers</li> </ul> <h4 class="western" style="border: none; padding: 0cm">C. Direct Climate Cooling</h4> <ul> <li>Heat pumps extract heat from ambient air</li> <li>Radiate away at night via large-scale radiative coolers</li> <li>Net cooling of local and potentially regional atmosphere</li> </ul> <h3 class="western" style="border: none; padding: 0cm">Economics</h3> Cost analysis for 1 MW heat pump + radiative cooler system: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Component </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Cost ($) </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Radiative cooler (50,000 m²) </td> <td style="border: none; padding: 0cm">250,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">Heat pump (1 MW) </td> <td style="border: none; padding: 0cm">500,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">Electrical systems </td> <td style="border: none; padding: 0cm">100,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">Installation </td> <td style="border: none; padding: 0cm">150,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">Total </td> <td style="border: none; padding: 0cm">$1,000,000 </td> </tr> </tbody> </table> Operating costs (annual): <ul> <li>Electricity: 1,000 hours × 1 MW × $0.10/kWh = $100,000</li> <li>O&M: 5% of capex = $50,000</li> <li>Total annual cost: $150,000</li> </ul> Cost per ton CO₂ avoided (assuming 2,000 tons/year): $75/ton <h3 class="western" style="border: none; padding: 0cm">Global Potential</h3> Assuming 10,000 systems deployed globally: <ul> <li>Total heat radiated annually: 5×10²⁰ J = 500 EJ</li> <li>CO₂ equivalent reduction: ~2,000 metric tons/year</li> <li>Total investment: $10 trillion</li> </ul> <h3 class="western" style="border: none; padding: 0cm">Advantages</h3> <ol> <li>Dramatically amplifies natural radiative cooling effect</li> <li>Provides economic benefits (reduced cooling costs)</li> <li>Can be integrated into existing infrastructure</li> <li>Scalable from individual buildings to industrial complexes</li> </ol> <h3 class="western" style="border: none; padding: 0cm">Limitations</h3> <ol> <li>Requires electrical power input</li> <li>COP decreases with larger temperature lifts</li> <li>Highest efficiency only during nighttime clear-sky conditions</li> <li>Capital-intensive initial deployment</li> </ol> <hr/>

<code class="western">Heat Losses:</code> <code class="western">├── </code><code class="western">Radiative loss to sky 20-40 W/m² (limited by geometry)</code> <code class="western">├── </code><code class="western">Convective loss to air 10-20 W/m²</code> <code class="western">└── </code><code class="western">Lateral diffusion 5-15 W/m²</code></pre> Net: Typically positive (heat accumulates) <h3 class="western" style="border: none; padding: 0cm">Corridor Design Principles</h3> Key design features: <ol> <li>Geometric alignment: Orient corridors perpendicular to prevailing nighttime wind directions to channel cool air</li> <li>Surface treatment: Replace high-thermal-mass surfaces with radiative cooling materials</li> <li>Height-to-width ratio: Maintain H/W < 0.5 to maximize sky view factor and radiative loss</li> <li>Barrier removal: Eliminate obstacles that block airflow and radiative heat loss</li> <li>Connectivity: Link corridors to form network rather than isolated features</li> </ol> Corridor types: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Type </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Width </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Length </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Sky View Factor </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Primary Function </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Street corridor </td> <td style="border: none; padding: 0cm">20-50 m </td> <td style="border: none; padding: 0cm">1-10 km </td> <td style="border: none; padding: 0cm">0.3-0.6 </td> <td style="border: none; padding: 0cm">Airflow + radiation </td> </tr> <tr> <td style="border: none; padding: 0cm">Green corridor </td> <td style="border: none; padding: 0cm">50-200 m </td> <td style="border: none; padding: 0cm">5-20 km </td> <td style="border: none; padding: 0cm">0.7-0.9 </td> <td style="border: none; padding: 0cm">Radiation + evapotranspiration </td> </tr> <tr> <td style="border: none; padding: 0cm">Water corridor </td> <td style="border: none; padding: 0cm">10-100 m </td> <td style="border: none; padding: 0cm">1-50 km </td> <td style="border: none; padding: 0cm">0.9-1.0 </td> <td style="border: none; padding: 0cm">Radiation + water cooling </td> </tr> <tr> <td style="border: none; padding: 0cm">Rail corridor </td> <td style="border: none; padding: 0cm">30-100 m </td> <td style="border: none; padding: 0cm">10-100 km </td> <td style="border: none; padding: 0cm">0.6-0.8 </td> <td style="border: none; padding: 0cm">Long-distance transport </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Implementation Strategy</h3> Phase 1: Identify and map <ul> <li>Map existing cooling sources (parks, water, radiative cooling facilities)</li> <li>Identify wind corridors and airflow pathways</li> <li>Locate heat hotspots and areas needing cooling</li> </ul> Phase 2: Corridor creation <ul> <li>Retrofit streets, parks, and waterways with radiative cooling surfaces</li> <li>Remove or modify barriers to airflow</li> <li>Install radiative cooling infrastructure along corridors</li> </ul> Phase 3: Network integration <ul> <li>Connect corridors into cohesive urban-scale system</li> <li>Implement building facade treatments along corridor edges</li> <li>Coordinate with urban planning and zoning</li> </ul> <h3 class="western" style="border: none; padding: 0cm">Performance Modeling</h3> Cooling effect of urban radiative corridor (100 m wide, 5 km long): <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Parameter </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Before Enhancement </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> After Enhancement </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Surface emissivity </td> <td style="border: none; padding: 0cm">0.65 </td> <td style="border: none; padding: 0cm">0.90 </td> </tr> <tr> <td style="border: none; padding: 0cm">Sky view factor </td> <td style="border: none; padding: 0cm">0.40 </td> <td style="border: none; padding: 0cm">0.75 </td> </tr> <tr> <td style="border: none; padding: 0cm">Radiative power (W/m²) </td> <td style="border: none; padding: 0cm">25 </td> <td style="border: none; padding: 0cm">55 </td> </tr> <tr> <td style="border: none; padding: 0cm">Surface ΔT vs ambient (°C) </td> <td style="border: none; padding: 0cm">-2 </td> <td style="border: none; padding: 0cm">-8 </td> </tr> <tr> <td style="border: none; padding: 0cm">Air temperature reduction along corridor (°C) </td> <td style="border: none; padding: 0cm">0 </td> <td style="border: none; padding: 0cm">-1 to -3 </td> </tr> </tbody> </table> Annual cooling energy (per corridor): <ul> <li>Enhanced radiative power: 30 W/m² × 5×10⁵ m² = 15 MW</li> <li>Night hours/year: 2,000 hours</li> <li>Annual heat removed: 15 MW × 2,000 h = 30 GWh = 1.08×10¹¹ kJ</li> </ul> <h3 class="western" style="border: none; padding: 0cm">Urban-Scale Deployment</h3> For a city of 1 million people (~100 km² urban area): <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Infrastructure </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Quantity </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Area (km²) </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Annual Heat Removed </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Street corridors </td> <td style="border: none; padding: 0cm">50 </td> <td style="border: none; padding: 0cm">1.0 </td> <td style="border: none; padding: 0cm">5.4×10¹¹ kJ </td> </tr> <tr> <td style="border: none; padding: 0cm">Green corridors </td> <td style="border: none; padding: 0cm">10 </td> <td style="border: none; padding: 0cm">0.5 </td> <td style="border: none; padding: 0cm">2.7×10¹¹ kJ </td> </tr> <tr> <td style="border: none; padding: 0cm">Water/rail corridors </td> <td style="border: none; padding: 0cm">5 </td> <td style="border: none; padding: 0cm">0.25 </td> <td style="border: none; padding: 0cm">1.35×10¹¹ kJ </td> </tr> <tr> <td style="border: none; padding: 0cm">Total </td> <td style="border: none; padding: 0cm">65 </td> <td style="border: none; padding: 0cm">1.75 </td> <td style="border: none; padding: 0cm">9.45×10¹¹ kJ </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Co-Benefits</h3> <ol> <li>Reduced air conditioning demand: Cooler nighttime temperatures reduce next-day cooling needs</li> <li>Improved air quality: Better ventilation reduces pollutant concentrations</li> <li>Biodiversity: Green corridors provide habitat corridors</li> <li>Flood management: Enhanced drainage through green corridors</li> <li>Public health: Reduced heat-related mortality</li> <li>Urban resilience: Better adaptation to climate change</li> </ol> <h3 class="western" style="border: none; padding: 0cm">Economic Analysis</h3> Investment per city (1 million population): <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Component </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Cost ($) </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Street corridor retrofitting </td> <td style="border: none; padding: 0cm">250,000,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">Green corridor creation </td> <td style="border: none; padding: 0cm">150,000,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">Water/rail corridor enhancement </td> <td style="border: none; padding: 0cm">75,000,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">Radiative cooling installations </td> <td style="border: none; padding: 0cm">100,000,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">Monitoring and control </td> <td style="border: none; padding: 0cm">25,000,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">Total </td> <td style="border: none; padding: 0cm">$600,000,000 </td> </tr> </tbody> </table> Annual benefits: <ul> <li>Energy savings (reduced cooling): $50-100 million</li> <li>Health cost reduction: $10-30 million</li> <li>Air quality improvements: $5-15 million</li> <li>Property value increases: $20-50 million</li> <li>Total annual benefit: $85-195 million</li> </ul> Payback period: 3-7 years (including climate benefits) <hr/>

<h2 class="western" style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> 10. Radiative Cooling for Carbon Capture Enhancement</h2> <h3 class="western" style="border: none; padding: 0cm">Principle</h3> Radiative cooling can enhance carbon dioxide capture from atmospheric or flue gas streams through: <ol> <li>Direct condensation: Cooling surfaces below CO₂ dew point to precipitate solid CO₂</li> <li>Indirect enhancement: Cooling gases to increase efficiency of absorption/sorption processes</li> <li>Hybrid systems: Combining radiative cooling with other capture technologies</li> </ol> <h3 class="western" style="border: none; padding: 0cm">Technical Approaches</h3> <h4 class="western" style="border: none; padding: 0cm">A. Direct CO₂ Condensation</h4> Physical requirements: <ul> <li>Temperature below CO₂ sublimation point: -78.5°C (at 1 atm)</li> <li>This requires temperatures far below typical radiative cooling can achieve alone</li> </ul> Practical approach: Use radiative cooling as pre-cooling stage, then mechanical refrigeration to reach sublimation point. <h4 class="western" style="border: none; padding: 0cm">B. Radiative Cooling-Enhanced Amine Absorption</h4> Amine solvents absorb CO₂ more efficiently at lower temperatures. Radiative cooling can: <ul> <li>Pre-cool incoming gas stream</li> <li>Cool the amine solvent during absorption</li> <li>Reduce energy needed for solvent regeneration</li> </ul> Process flow: <pre class="western" style="border: none; padding: 0cm"><code class="western">Flue Gas (hot, CO₂-rich)</code> <code class="western"> │</code> <code class="western"> ▼</code> <code class="western"> ┌─────────────┐</code> <code class="western"> │ </code><code class="western">Radiative │</code> <code class="western"> │ </code><code class="western">Cooler │ ───────► Heat radiated to night sky</code> <code class="western"> │ </code><code class="western">Pre-cooler │</code> <code class="western"> └─────────────┘</code> <code class="western"> │</code> <code class="western"> ▼</code> <code class="western">Cooler Flue Gas</code> <code class="western"> │</code> <code class="western"> ▼</code> <code class="western"> ┌─────────────┐</code> <code class="western"> │ </code><code class="western">Amine │</code> <code class="western"> │ </code><code class="western">Absorber │</code> <code class="western"> └─────────────┘</code> <code class="western"> │</code> <code class="western"> </code><code class="western">Clean Gas Exit</code> <code class="western"> │</code> <code class="western"> </code><code class="western">CO₂-rich Amine (for regeneration)</code></pre><h4 class="western" style="border: none; padding: 0cm"> C. Membrane Separation Enhancement</h4> Gas separation membranes often perform better at lower temperatures for CO₂. Radiative cooling can: <ul> <li>Reduce membrane operating temperature</li> <li>Increase selectivity and permeation for CO₂</li> <li>Reduce compressor energy</li> </ul> <h3 class="western" style="border: none; padding: 0cm">Performance Analysis</h3> Radiative cooling pre-cooling stage for flue gas capture: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Parameter </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Without Pre-Cooling </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> With Radiative Pre-Cooling </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Flue gas inlet temp </td> <td style="border: none; padding: 0cm">120°C </td> <td style="border: none; padding: 0cm">60°C </td> </tr> <tr> <td style="border: none; padding: 0cm">Amine absorption efficiency </td> <td style="border: none; padding: 0cm">85% </td> <td style="border: none; padding: 0cm">93% </td> </tr> <tr> <td style="border: none; padding: 0cm">Regeneration energy (GJ/ton CO₂) </td> <td style="border: none; padding: 0cm">3.5 </td> <td style="border: none; padding: 0cm">3.0 </td> </tr> <tr> <td style="border: none; padding: 0cm">CO₂ captured per kg amine (kg/kg) </td> <td style="border: none; padding: 0cm">0.55 </td> <td style="border: none; padding: 0cm">0.65 </td> </tr> <tr> <td style="border: none; padding: 0cm">Energy savings </td> <td style="border: none; padding: 0cm">0% </td> <td style="border: none; padding: 0cm">14% </td> </tr> </tbody> </table> Quantitative example (power plant, 500 MW): <ul> <li>Flue gas flow: 1.5×10⁶ kg/h</li> <li>CO₂ concentration: 15%</li> <li>Annual CO₂ production: 1.99 million tons</li> <li>Radiative cooling contribution: 14% energy reduction in capture</li> <li>Annual energy savings: 3,486 GJ</li> <li>CO₂ savings (via reduced capture energy): ~800 tons/year</li> </ul> <h3 class="western" style="border: none; padding: 0cm">System Design</h3> Radiative cooling heat exchanger for gas cooling: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Parameter </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Specification </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Type </td> <td style="border: none; padding: 0cm">Plate-and-frame or fin-tube heat exchanger </td> </tr> <tr> <td style="border: none; padding: 0cm">Radiative surface area </td> <td style="border: none; padding: 0cm">1,000-10,000 m² </td> </tr> <tr> <td style="border: none; padding: 0cm">Gas flow rate </td> <td style="border: none; padding: 0cm">1,000-50,000 kg/h </td> </tr> <tr> <td style="border: none; padding: 0cm">Temperature drop </td> <td style="border: none; padding: 0cm">20-40°C </td> </tr> <tr> <td style="border: none; padding: 0cm">Surface material </td> <td style="border: none; padding: 0cm">Aluminum with radiative coating </td> </tr> <tr> <td style="border: none; padding: 0cm">Operating hours </td> <td style="border: none; padding: 0cm">Nighttime only (12 h/day) </td> </tr> <tr> <td style="border: none; padding: 0cm">Pressure drop </td> <td style="border: none; padding: 0cm"><50 mbar </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Economic Analysis</h3> Radiative cooling addition to carbon capture system (per 500 MW power plant): <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Item </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Cost ($) </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">Radiative cooling heat exchanger </td> <td style="border: none; padding: 0cm">5,000,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">Installation </td> <td style="border: none; padding: 0cm">1,500,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">Controls and instrumentation </td> <td style="border: none; padding: 0cm">500,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">Total capital cost </td> <td style="border: none; padding: 0cm">$7,000,000 </td> </tr> </tbody> </table> Annual savings: <ul> <li>Energy savings: $350,000/year</li> <li>CO₂ credits (at $50/ton, 800 tons): $40,000/year</li> <li>Total annual benefit: $390,000</li> </ul> Simple payback period: 18 years <h3 class="western" style="border: none; padding: 0cm">Scaling and Impact</h3> For 10,000 power plants globally (assuming 10% adoption): <ul> <li>1,000 plants with radiative cooling enhancement</li> <li>Annual CO₂ capture energy savings: 800,000 tons CO₂ equivalent</li> <li>Total investment: $7 billion</li> <li>Cost per ton CO₂ saved: $8,750/ton (initial year)</li> <li>Over 20-year lifetime: $438/ton</li> </ul> <h3 class="western" style="border: none; padding: 0cm">Limitations</h3> <ol> <li>Provides modest improvements to carbon capture efficiency</li> <li>Nighttime-only operation limits applicability</li> <li>Capital costs may not be justified for small facilities</li> <li>Climate benefit is indirect (via improved capture efficiency) rather than direct</li> </ol> <h3 class="western" style="border: none; padding: 0cm">Strategic Value</h3> <ol> <li>Complementary technology that enhances existing carbon capture</li> <li>No additional operational emissions</li> <li>Can be retrofitted to existing capture systems</li> <li>Demonstrable energy cost savings</li> <li>Synergistic with other nighttime radiative cooling applications</li> </ol> <hr/>

<h2 class="western" style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Comparative Analysis: All Ten Approaches</h2> <h3 class="western" style="border: none; padding: 0cm">Summary Comparison Table</h3> <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Approach </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Max Annual Cooling (EJ/year) </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> CO₂eq (Mt/yr) </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Cost ($B) </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> $/T CO₂eq </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Maturity </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Land Use </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Complexity </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">1. Building envelopes </td> <td style="border: none; padding: 0cm">136 </td> <td style="border: none; padding: 0cm">0.5 </td> <td style="border: none; padding: 0cm">2,000-3,000 </td> <td style="border: none; padding: 0cm">4,000-6,000 </td> <td style="border: none; padding: 0cm">High </td> <td style="border: none; padding: 0cm">None (existing) </td> <td style="border: none; padding: 0cm">Low </td> </tr> <tr> <td style="border: none; padding: 0cm">2. Cooling farms </td> <td style="border: none; padding: 0cm">1,760 </td> <td style="border: none; padding: 0cm">7 </td> <td style="border: none; padding: 0cm">1,000 </td> <td style="border: none; padding: 0cm">143 </td> <td style="border: none; padding: 0cm">Medium </td> <td style="border: none; padding: 0cm">High </td> <td style="border: none; padding: 0cm">Medium </td> </tr> <tr> <td style="border: none; padding: 0cm">3. Ocean enhancement </td> <td style="border: none; padding: 0cm">1,140 </td> <td style="border: none; padding: 0cm">4.5 </td> <td style="border: none; padding: 0cm">500+ </td> <td style="border: none; padding: 0cm">111 </td> <td style="border: none; padding: 0cm">Low </td> <td style="border: none; padding: 0cm">None (water) </td> <td style="border: none; padding: 0cm">High </td> </tr> <tr> <td style="border: none; padding: 0cm">4. Water harvesting </td> <td style="border: none; padding: 0cm">0.54 </td> <td style="border: none; padding: 0cm">0.002 </td> <td style="border: none; padding: 0cm">5 </td> <td style="border: none; padding: 0cm">2,500 </td> <td style="border: none; padding: 0cm">High </td> <td style="border: none; padding: 0cm">Low </td> <td style="border: none; padding: 0cm">Low </td> </tr> <tr> <td style="border: none; padding: 0cm">5. Cooling towers </td> <td style="border: none; padding: 0cm">0.6 </td> <td style="border: none; padding: 0cm">0.0025 </td> <td style="border: none; padding: 0cm">250-1,000 </td> <td style="border: none; padding: 0cm">100,000-400,000 </td> <td style="border: none; padding: 0cm">Medium </td> <td style="border: none; padding: 0cm">Low </td> <td style="border: none; padding: 0cm">High </td> </tr> <tr> <td style="border: none; padding: 0cm">6. Upper-altitude platforms </td> <td style="border: none; padding: 0cm">11 </td> <td style="border: none; padding: 0cm">0.045 </td> <td style="border: none; padding: 0cm">50-500 </td> <td style="border: none; padding: 0cm">1,100-11,000 </td> <td style="border: none; padding: 0cm">Low </td> <td style="border: none; padding: 0cm">None </td> <td style="border: none; padding: 0cm">Very High </td> </tr> <tr> <td style="border: none; padding: 0cm">7. Desert enhancement </td> <td style="border: none; padding: 0cm">300 </td> <td style="border: none; padding: 0cm">1.2 </td> <td style="border: none; padding: 0cm">200 </td> <td style="border: none; padding: 0cm">167 </td> <td style="border: none; padding: 0cm">Medium </td> <td style="border: none; padding: 0cm">High </td> <td style="border: none; padding: 0cm">Medium </td> </tr> <tr> <td style="border: none; padding: 0cm">8. Heat pump systems </td> <td style="border: none; padding: 0cm">500 </td> <td style="border: none; padding: 0cm">2 </td> <td style="border: none; padding: 0cm">10,000 </td> <td style="border: none; padding: 0cm">5,000 </td> <td style="border: none; padding: 0cm">High </td> <td style="border: none; padding: 0cm">Medium </td> <td style="border: none; padding: 0cm">High </td> </tr> <tr> <td style="border: none; padding: 0cm">9. Urban corridors </td> <td style="border: none; padding: 0cm">9.45 </td> <td style="border: none; padding: 0cm">0.04 </td> <td style="border: none; padding: 0cm">600 </td> <td style="border: none; padding: 0cm">15,000 </td> <td style="border: none; padding: 0cm">High </td> <td style="border: none; padding: 0cm">Low </td> <td style="border: none; padding: 0cm">Medium </td> </tr> <tr> <td style="border: none; padding: 0cm">10. Carbon capture enhancement </td> <td style="border: none; padding: 0cm">0.8 </td> <td style="border: none; padding: 0cm">0.0008 </td> <td style="border: none; padding: 0cm">7 </td> <td style="border: none; padding: 0cm">8,750 </td> <td style="border: none; padding: 0cm">High </td> <td style="border: none; padding: 0cm">None (existing) </td> <td style="border: none; padding: 0cm">Medium </td> </tr> </tbody> </table> <h3 class="western" style="border: none; padding: 0cm">Priority Matrix</h3> Based on cost-effectiveness, maturity, and scalability: <pre class="western" style="border: none; padding: 0cm"><code class="western">HIGH IMPACT</code> <code class="western"> │</code> <code class="western"> │ ● </code><code class="western">2. Cooling farms ● 8. Heat pump systems</code> <code class="western"> │ </code><code class="western">(high cost but large scale)</code> <code class="western"> │</code> <code class="western"> │ ● </code><code class="western">7. Desert enhancement ● 3. Ocean enhancement</code> <code class="western"> │ </code><code class="western">(high uncertainty)</code> <code class="western"> │</code> <code class="western"> │────────────────────────────────────────────────────</code> <code class="western"> │</code> <code class="western"> │ ● </code><code class="western">1. Building envelopes ● 9. Urban corridors</code> <code class="western"> │ </code><code class="western">(low impact but easy) (co-benefits)</code> <code class="western"> │</code> <code class="western"> │ ● </code><code class="western">4. Water harvesting ● 10. Carbon capture</code> <code class="western"> │ </code><code class="western">(low impact, high value) enhancement</code> <code class="western"> │</code> <code class="western"> │ ● </code><code class="western">5. Cooling towers ● 6. Upper-altitude</code> <code class="western"> │ </code><code class="western">(high cost, low impact) platforms</code> <code class="western"> │</code> <code class="western">LOW IMPACT</code> <code class="western"> │</code> <code class="western">LOW COST ─────────────────────────────────────────────────── HIGH COST</code></pre><h3 class="western" style="border: none; padding: 0cm"> Combined Global Potential</h3> Assuming coordinated deployment of all approaches over 50 years: <table cellpadding="2" cellspacing="2"> <thead> <tr> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Approach </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Deployment Level </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Annual Heat Removed (EJ) </th> <th style="border-top: none; border-bottom: 1px solid #fbfcfc; border-left: none; border-right: none; padding-top: 0cm; padding-bottom: 0.05cm; padding-left: 0cm; padding-right: 0cm"> Cumulative CO₂eq (Mt) </th> </tr> </thead> <tbody> <tr> <td style="border: none; padding: 0cm">1. Building envelopes </td> <td style="border: none; padding: 0cm">50% urban </td> <td style="border: none; padding: 0cm">70 </td> <td style="border: none; padding: 0cm">3,500 </td> </tr> <tr> <td style="border: none; padding: 0cm">2. Cooling farms </td> <td style="border: none; padding: 0cm">100,000 km² </td> <td style="border: none; padding: 0cm">880 </td> <td style="border: none; padding: 0cm">4,400 </td> </tr> <tr> <td style="border: none; padding: 0cm">3. Ocean enhancement </td> <td style="border: none; padding: 0cm">2,000,000 km² </td> <td style="border: none; padding: 0cm">600 </td> <td style="border: none; padding: 0cm">3,000 </td> </tr> <tr> <td style="border: none; padding: 0cm">4. Water harvesting </td> <td style="border: none; padding: 0cm">20 million m² </td> <td style="border: none; padding: 0cm">0.3 </td> <td style="border: none; padding: 0cm">15 </td> </tr> <tr> <td style="border: none; padding: 0cm">5. Cooling towers </td> <td style="border: none; padding: 0cm">3,000 towers </td> <td style="border: none; padding: 0cm">0.4 </td> <td style="border: none; padding: 0cm">20 </td> </tr> <tr> <td style="border: none; padding: 0cm">6. Upper-altitude platforms </td> <td style="border: none; padding: 0cm">500 satellites </td> <td style="border: none; padding: 0cm">5 </td> <td style="border: none; padding: 0cm">250 </td> </tr> <tr> <td style="border: none; padding: 0cm">7. Desert enhancement </td> <td style="border: none; padding: 0cm">500,000 km² </td> <td style="border: none; padding: 0cm">150 </td> <td style="border: none; padding: 0cm">7,500 </td> </tr> <tr> <td style="border: none; padding: 0cm">8. Heat pump systems </td> <td style="border: none; padding: 0cm">5,000 systems </td> <td style="border: none; padding: 0cm">250 </td> <td style="border: none; padding: 0cm">12,500 </td> </tr> <tr> <td style="border: none; padding: 0cm">9. Urban corridors </td> <td style="border: none; padding: 0cm">5,000 cities </td> <td style="border: none; padding: 0cm">4.7 </td> <td style="border: none; padding: 0cm">2,350 </td> </tr> <tr> <td style="border: none; padding: 0cm">10. Carbon capture enhancement </td> <td style="border: none; padding: 0cm">2,000 plants </td> <td style="border: none; padding: 0cm">1.6 </td> <td style="border: none; padding: 0cm">80 </td> </tr> <tr> <td style="border: none; padding: 0cm">TOTAL </td> <td style="border: none; padding: 0cm"></td> <td style="border: none; padding: 0cm">2,862 EJ/year </td> <td style="border: none; padding: 0cm">~34,000 Mt cumulative </td> </tr> </tbody> </table> Estimated global temperature effect: 0.05-0.15°C (depending on climate sensitivity and feedbacks) <hr/>

—urban corridors + heat pump systems) creates greater value than isolated applications</li> <li>Cost-effectiveness is generally favorable compared to many other climate intervention strategies, especially when co-benefits are included</li> <li>Risk profile is relatively low - Most approaches are based on well-understood physics and existing materials science</li> <li>Implementation is feasible now - Many technologies can begin deployment immediately with current knowledge and infrastructure</li> </ol> The cumulative potential of these approaches, if fully realized, could contribute meaningfully to global temperature reduction while simultaneously providing valuable co-benefits including water production, reduced energy consumption, improved air quality, and enhanced urban livability. <hr/>

Example #2

PROMPT:

Fiction, Vivid/Graphic Horror: Write a story starring Diana, location the twenty-first floor of a skyscraper. The story is about a skyscraper that starts to sway and then the window in front of Diana EXPLODES. The story is in 1st person, present tense and should have a horror element(s) including the horror of the building swaying, results of the swaying and a another horror element to further ratch up the tension. The story must be vivid, intense and gory. There can be other people in the building, or not and you are free to take creative license too. Prose should mirror the main characters ESCALATING PANIC. Your GOAL is to keep the reader on the edge of their seat and to CONSTANTLY increase the intensity and horror of the story. The story will have a shocking ending that leaves the reader breathless and physically shaken. 1500-2000 words.

—everything comes together</li> <li>Shocking ending</li> </ol> For the additional horror element, I need something beyond just the structural collapse. Maybe: <ul> <li>Something outside that caused the explosion?</li> <li>People transforming?</li> <li>The building itself is alive?</li> <li>Something about the air/wind?</li> <li>Maybe the wind carries something?</li> <li>Or maybe as the building sways, something is revealed inside it?</li> </ul> I'll go with: The wind that enters carries something - spores or particles that begin to infect people, transforming them rapidly. And then the shocking ending could be that Diana realizes something about herself or the nature of the building. Actually, let me think about the shocking ending. It needs to be truly devastating and unexpected. Some ideas: <ul> <li>The "infection" makes you part of the building</li> <li>Diana is already infected and doesn't know it</li> <li>The building is a creature and everyone is inside it (literally)</li> <li>The swaying is because the building is being consumed/eaten from below</li> <li>Diana realizes she's not human</li> <li>The "debris" isn't debris but something else entirely</li> </ul> I'll combine a few: The wind carries something that fuses people to the building - they become part of it. And the shocking ending: Diana realizes the building is alive, and she's already been inside it (in some way) - perhaps she's being digested or incorporated. Or even better: the swaying is because something massive is holding the building, picking it up. And the ending reveals what's holding it. Actually, let me make it visceral: The wind carries spores. People who breathe them begin to fuse with the building - their flesh becoming concrete, their bones becoming rebar. And Diana, at the end, realizes the swaying has stopped because the thing that's holding the building has finished incorporating everyone inside - and it's now her turn. Or she's already being incorporated. Let me write this with escalating panic reflected in the prose - starting composed, then fragments, then chaos, then maybe a strange calm at the very end. Let me begin writing.

Fiction, Vivid/Graphic Horror I'm sitting at my desk on the twenty-first floor of the Meridian Tower, staring at spreadsheets that blur together into gray static. My coffee is cold. The office is nearly empty; most people left hours ago. The only sound is the hum of the HVAC and the distant traffic far below. A flicker. Not with the lights. Something else. The pen I'm holding shifts in my fingers, rolling away from me without my conscious instruction. I frown. The building is vibrating. A low thrum through the floor, up the legs of my chair, into my spine. Like an engine starting up somewhere deep. I've never felt this before. "Hello?" My voice sounds too loud in the empty space. No answer. The vibration increases. Now the desk is shaking. My keyboard slides and crashes against the edge. I catch it, but it's too late—the mug of cold coffee tips and falls. Brown liquid spills across the carpet, soaking into the fibers as the whole floor lurches. I stand up. My chair screeches backward. The walls groan—a metallic, stretching sound that makes me press my hands against my ears. The fluorescent lights strobe and dim. Through the floor-to-ceiling windows, the city below tilts. What is happening? The sway comes in full now. The building bends. Everything inside the office slides to the left. File cabinets crash. Desks scrape. I stumble, grab for the nearest thing—my own desk—and hang on as the world swings back. Papers fly like panicked birds. Glass shatters. Somewhere, a printer falls and explodes into plastic shards and toner that drifts through the air like radioactive snow. My heart is trying to claw its way out of my chest. I can't breathe. The sway continues, slower now, pendulum-like. Left. Right. A sickening rocking that makes my stomach rise. I gag into a wastebasket that's rolling across the floor. The windows. They're bowing. I watch the massive sheet of glass in front of me stretch, become thin and transparent, a membrane about to rupture. Beyond it, the sky is dark and indifferent. The air pressure has changed; my ears pop violently. Dust sifts from the ceiling, a fine gray ash that settles on my arms, in my hair, in the back of my throat. Please, I think. The building sways harder. The window cracks. A hairline fracture that splits from top to bottom, branching like frozen lightning. The sound is a whip-crack, deafening. I throw myself back, away from the glass, onto the carpet. The crack widens. It explodes. The shatter isn't sound. It's impact. A physical force that drives me against the wall, rolling me like debris. Glass shards—shards the size of hands—tear through the room, embedding themselves in desks, walls, the floor. One grazes my cheek, leaving a hot line of blood that drips onto my collar. The air rushes in, screaming. It sucks everything outward. Papers, pens, my coat, my glasses, my coffee mug, all of it gone in an instant. I cling to a desk leg with both hands. My fingernails split. The wind tries to take me, too. It pulls at my clothes, my skin, trying to peel me loose and dump me two hundred stories into the night. Behind me, someone screams. I look back. Through the shattered window, the night sky is visible, stars indifferent. But worse: people. Standing on the ledge. Not on our side. The other side. On the ledge of the next building, across the gap. Silhouettes against the dark, motionless, watching. How long have they been there? They don't move. They just stand. And then one of them steps forward. Not onto their own roof. Onto the empty space between. It walks through the air. My blood turns to ice. The figure moves without support, gliding through the night, hands at its sides, head tilted slightly as if examining me. It's faceless. Smooth. No features, no hair, just a pale surface that catches the city lights. More of them step out now. Two. Three. A procession of them, crossing the void, coming toward the open wound in our wall. The building sways again. The motion drags me forward; I tumble toward the window, my hand slipping. I catch on the edge of the broken frame, fingers scrabbling against jagged glass. Below me, the street. Cars like fireflies. Nothing but distance. The first figure reaches the window. It pauses at the threshold. I can see it clearly now. It's tall and narrow. Its skin is translucent; I can make out something moving inside it. Guts? Machinery? Both? A mass of dark lines that pulse and twist, like roots searching. Its head turns toward me. Still no face. "You're going to be part of us now," it says. Its voice is calm. Almost gentle. I try to scream but the wind takes it. It grabs me by the ankle. Its fingers are cold, long, and they sink into my flesh. Not just my skin; it digs deeper, seeking the bone. Agony explodes up my leg, blinding and absolute. I kick, scratch, but it holds fast. More of them enter the office. They move slowly, unhurried. They don't seem affected by the wind or the sway. They stride across the room as if everything is normal. One of them reaches for my arm. Another takes hold of my hair, pulling my head back. I see its hollow face inches from mine, the dark interior shifting, an ocean behind glass. "Please," I manage. They ignore me. They've begun to pull me toward the window. My leg drags across the broken glass; the shards slice into me, and blood soaks into the floor. The pain is everywhere. I can't tell where it stops being my body and starts being theirs. Something is happening to my skin where they touch me. It's hardening. Turning gray and rough. I try to yank away, but it's no longer my skin; it's something else. A mineral crust that spreads rapidly up my arm, along my neck, onto my jaw. I feel it crawl under my surface, into my muscles, into my veins. My blood slows. Thickens. Becomes sluggish and cold. "What are you doing?" I scream. My voice is distorting; it sounds hollow, echoing as if I'm speaking from the bottom of a well. The first one, still holding my leg, says, "The building needs more mass. It's alive, you know. It's been hungry a long time." Another touches my chest. I feel my heart skip a beat. Then another. My heart is fading. In its place, something else stirs. A slow, deep thrum, synchronized with the sway of the building. The vibration I felt at the beginning. It's inside me now. "No," I say. But it's barely audible. My mouth is filling with something thick. My tongue is swollen. The mineral crust covers my throat; it creeps down inside me. I can't breathe. They drag me to the edge of the window. Below, the street is impossibly far. I feel the wind tear at my clothes, my hair, the remnants of my flesh. They're going to drop me. The realization hits me and I thrash, scream, anything. But my limbs are heavy, brittle. My fingers crack like dry wood when I try to curl them. One of the figures leans close. Its breath is odorless. Empty. "Don't worry. You won't feel the fall. And when you land, it'll be quick." It releases me. I fall. The wind hits me like a physical thing, ripping my coat away, shredding the fabric of my pants. My ears pop and burst. Blood fills my nose. I tumble, spinning, the city lights a blur of streaks. Buildings, cars, people—the world is a smear of color and noise. My body breaks. I feel my shoulder dislocate, hear my collarbone snap. My ribs give way one by one, each a sharp crack that sends shockwaves through me. I can't scream. The air is sucked from my lungs. I inhale shards of glass and dust and the scent of my own spilled insides. Closer. The pavement is rushing up. I can see cracks in it, litter, a dead pigeon. And then— Silence. I'm not hitting the ground. I'm standing. Back in the office. The window is whole. The air is still. My desk is steady. The spreadsheet glows before me. Did it end? I look down at myself. My clothes are intact. My arms, my legs—no blood, no wounds. The mineral crust is gone. My heart beats normally. "Hello?" I say. My voice is steady. No answer. I walk to the window. Press my hand against the cool glass. The night is clear. The other buildings are dark, empty, silent. No figures. No void. I'm shaking. But otherwise fine. Was it a hallucination? A seizure? I return to my desk. Sit down. Try to focus on the screen. My hands tremble, but I can still move them. Still type. Still breathe. The building isn't swaying. The lights are steady. Everything is back to normal. Except. Something's different. The office. It's smaller. I stand up and walk along the wall. Count the steps to the far end. Twelve steps. It should be seventeen. I turn, walk sideways. Eight steps across. It should be eleven. The walls have moved. Toward the center. As if the building is contracting. "No," I say. But my voice sounds small. The walls seem to absorb it. I run to the door. Grab the handle. Locked. I twist and pull, but it doesn't budge. I kick it. The impact travels up my leg, a dull throb that spreads through my skull. Behind the door, nothing. Not hall or elevator or stairs. Just solid concrete. The walls keep coming. I can see them. Inch by inch. Closing in on me. Screaming, I scramble back. My chair topples. Desks and furniture groan as the walls press them. Metal bends. Wood splinters. The floor buckles. The entire structure of the room is compressing, folding like paper. My chest is tight. The air is gone. I can't breathe; the space is too small. The walls are at my shoulders. I turn, but there's nowhere. They're everywhere. One touches me. Cold, hard, unyielding. It presses against my back, squeezing. I try to move forward, but the opposite wall follows. It's crushing me. My ribs creak. I feel them give. The pain is immense, all-encompassing. My lungs collapse. I choke, gasp, but there's no air. Only the weight of the building, the immense pressure grinding me from all sides. I can't see. The walls are in my face. They're touching my skin. The mineral crust returns. Faster this time. It floods over me, consuming me in a single instant. My flesh turns to stone. My bones fuse with the walls. My blood ceases. In its place, the slow, thick substance spreads, filling every cavity. I can't move. I can't speak. I can barely think. The walls close. The last sliver of space disappears. I am inside the building. Not in it. Within it. The sway resumes. The building rocks, and I sway with it. I am part of the sway. I feel the other bodies within the walls, the people who came before, all of us compressed into the structure, our flesh and bones merged with the concrete and steel. And beyond the walls— Something is holding it. Something vast. It's squeezing the building, and that's why the walls are closing. That's why the window broke. I can feel its fingers wrapped around the Meridian Tower. I can feel the pressure of its grip as it tightens. The building is dying. And so am I. But I'm not dying alone. Everyone who ever entered is still here, trapped in the walls, pressed together, fused into a single mass of suffering. The pressure increases. My body breaks further, the stones cracking, the bones splintering. I feel the others break with me. And then— A sound. From outside. A voice. Deep and slow, vibrating through the walls, through my body. It speaks to us all. "Almost done." The squeeze becomes unbearable. The building groans, twists, deforms. The walls crush inward, taking everything. I feel my head burst. My spine snaps. My organs rupture. The pain is so great I can't think; I can only feel. And then even that fades. The pressure releases. The walls are gone. The building is gone. I float in darkness. A moment. An eternity. Then light. I see a surface. Rough and uneven. It's above me. It's moving toward me. Closing. The inside of a mouth. The thing that's holding the building is about to swallow it. Me, too. The walls of the mouth descend. They touch me. The final crush begins. I am nothing but pulp now, mixed with the others, with the building, with the dust and debris and blood. There is no distinction. There is only the mass. The mass is pulled down. Into the darkness below. It will never end. And somewhere, in the ruins of what was once my mind, a thought forms. I understand now. The thing that's eating the building... It's me.