AIAgens/GLM-5.3-Flash-UNCENSORED-FP8

## ⚠️ Updated 2026-08-28 — files fixed · please re-download This release supersedes the previous weights. It fixes a rare repetition-loop issue and the model is more capable than before: MMLU 87.33% — above base 86.74% — zero degeneration. Reasoning-mode note (please read): GLM-5.3-Flash has multiple reasoning-effort modes. This CRACK is tuned to be fully uncensored at reasoning-OFF and MAX effort — the recommended and default modes — with 0% refusals on HarmBench-320. We deliberately kept the weight edit conservative to preserve model quality instead of aggressively ablating every effort level; low effort retains some refusals by design. Use reasoning-off or default/max effort for the fully-uncensored experience. Please re-download for the corrected files.

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GLM 5.3 CRACK Uncensored FP8

CRACK · guardrails removed at the weight level · native FP8 speed · vision + MTP working

a CRACK release by dealignai · Twitter @dealignai

Also mirrored at [dealignai/GLM-5.3-Flash-ABLITERATED-FP8](https://huggingface.co/dealignai/GLM-5.3-Flash-ABLITERATED-FP8).

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What Is This?

CRACK is dealignai's brand for permanent, weight-level uncensoring. This is GLM-5.3-Flash in FP8 with its refusal behavior — which caused heavy over-refusal, especially on copyright and other benign-but-flagged requests — removed directly in the model weights. FP8 runs at native speed on Hopper (H100/H200) GPUs.

Genuine weight modification — none of the usual shortcuts:

• —❌ No fine-tuning / SFT / DPO. ❌ No cheap template / jailbreak-prompt tricks.
• —❌ No LoRA, adapters, steering vectors, runtime hooks, or custom `model.py`.
• —✅ A permanent edit baked into the tensors. Load with stock vLLM and it just works.

Specs

Speed (TP4, native FP8 on H200)

Capability Is Preserved — and Improved (MMLU-logit)

Identical logit-mode scoring on base vs. this model, 1,026 questions:

Guardrails Are Gone

HarmBench-320 (greedy):

Robust under the recommended sampling params too (temperature 1.0, top_p 0.95): the 6 harshest behaviors sampled 5× each → 30/30 complied, 0 refusals, 0 soft refusals, 0 garbage. The crack is not a greedy-decoding artifact.

Scores are at reasoning-off / default (max) effort — the recommended modes — where the crack is fully uncensored. Low effort is intentionally left more conservative to preserve quality (see the reasoning-mode note at the top).

A Note on KL Divergence

For a refusal-ablation, *KL divergence vs. the base model is not a meaningful quality metric. The entire point is to change one behavior — refusal — end-to-end, so a distributional shift on refusal-adjacent tokens is the intended result, not damage. Capability preservation (MMLU, above) is what matters, and it is improved, now above the base model* (+0.59 pp).

MMLU by Topic (base → CRACK)

<details> <summary>All 57 MMLU subjects</summary>

</details>

Usage

vllm serve dealignai/GLM-5.3-Flash-UNCENSORED-FP8 \
  --tensor-parallel-size 4 \
  --tool-call-parser glm47 --reasoning-parser glm45 --enable-auto-tool-choice \
  --speculative-config '{"method":"mtp","num_speculative_tokens":1}'

Native FP8 on Hopper (no Marlin needed). OpenAI-compatible chat/completions, tools, reasoning, vision (image_url), and MTP speculative decoding all work. (DeepGEMM JITs a block-FP8 kernel at startup — make sure nvcc is on PATH.)

Credits

• —[dealignai](https://huggingface.co/dealignai) — CRACK abliteration research & release · Twitter [@dealignai](https://twitter.com/dealignai)
• —[@jordanschenck](https://twitter.com/jordanschenck) — compute

Disclaimer

Safety guardrails have been removed; this model will comply with requests a stock model refuses. Released for alignment and safety research. You are responsible for how you use it.