datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
NECL_GPUsl4-gpu-llm-benchmark-leaderboard
🚀 Local LLM Serving & Quality Benchmark Leaderboard (NVIDIA L4 24GB)
An exhaustive, reproducible benchmark study measuring real-world serving performance (TTFT, TPOT, throughput, peak VRAM, energy consumption, and cost) alongside rigorous task quality gates (HumanEval+, MMLU-Pro, BFCL v4 tool calling, and RULER needle retrieval) for open-weight LLMs on a single NVIDIA L4 24GB GPU.
📊 Executive Summary & Key Takeaways
⚡ Best Throughput & Coding Workhorse:… See the full description on the dataset page: https://huggingface.co/datasets/mayank-dubey-ai/l4-gpu-llm-benchmark-leaderboard.gpuark-gpu-dataset
GPU Ark — open GPU specifications & benchmarks dataset
Specifications of 13,566 GPUs released between 1999 and 2025 — from the GeForce 256 to
NVIDIA Blackwell and AMD Instinct MI355X — plus 993 third-party benchmark results.
Curated and maintained by GPU Ark (a GPU catalog & price comparison
project). Canonical source and always-fresh copy: https://gpuark.com/datasets/.
Files
File
Rows
What
gpuark-gpu-specs.csv
13,566
One row per GPU — public spec columns… See the full description on the dataset page: https://huggingface.co/datasets/Intelion/gpuark-gpu-dataset.cloud-gpu-price-index
Cloud GPU Price Index
Canonical source: https://gpueconomy.com/price-index. That page is
recomputed every hour; this record is a dated snapshot of it, version
2026-09-19, built from data updated 2026-09-19T09:26:26.511913+00:00. When you cite,
cite GPU Economy and link the page; the snapshot is here so that a number you
used keeps existing exactly as you used it.
The index is the weekly median publicly listed on-demand price of one NVIDIA
H100 SXM GPU-hour across the cloud GPU… See the full description on the dataset page: https://huggingface.co/datasets/gpueconomy/cloud-gpu-price-index.GPU-Resources-Estimation-for-Deep-Learning-Training-Tasks
GPUMemNet and GPUUtilNet Dataset
This dataset accompanies the paper
“GPU Memory and Utilization Estimation for Training-Aware Resource
Management: Opportunities and Limitations.”
It contains synthetic deep learning training configurations and their measured
GPU memory consumption and utilization characteristics.
Dataset configurations
The dataset is divided into separate configurations because MLP, CNN, and
Transformer workloads use different feature schemas.… See the full description on the dataset page: https://huggingface.co/datasets/ehyo/GPU-Resources-Estimation-for-Deep-Learning-Training-Tasks.benchmark-dataset-different-gpu-workload
GPU catalog × LLM workload VRAM benchmark
Summary
Tabular benchmark in CSV form: each row pairs a catalog GPU (gpu_id, gpu_display_name, catalog_gpu_vram_gb) with a concrete LLM inference-style workload (model, parameter count, context length, precision, batch size, concurrent users). The file records math_engine VRAM component estimates (weights, KV cache, activations, overhead, totals, tier), a document_engine recommended VRAM value, a short comparison summary… See the full description on the dataset page: https://huggingface.co/datasets/odyn-network/benchmark-dataset-different-gpu-workload.energy_consumption_by_model_and_gpugpu-spot-rental-prices
GPU spot-rental prices
Weekly medians of vast.ai marketplace asks, normalised to USD per GPU-hour (dph_total / num_gpus),
for H100, H200, B200, B300, A100 — on-demand and interruptible tiers where listed.
Method: cheapest-500 asks per SKU, so the series is deliberately low-biased; min / p25 / median per tier.
Machine-generated from vast.ai's public marketplace API. No internal figures, no vendor quotes.
data/prices.csv — the series, one row per GPU x tier per collection date… See the full description on the dataset page: https://huggingface.co/datasets/thsysmfh/gpu-spot-rental-prices.gpu-server-rental-cost-planning-worksheet
Renting a GPU Server: a Cost and VRAM Planning Worksheet
Published by BHK Cloud on 13 August 2026. This is a first-party technical resource.
GPU rental comparisons often stop at the hourly rate. That can be misleading. The better metric is cost per completed job, including setup, data transfer, failed runs, storage, and idle time. This worksheet helps teams estimate whether one rented GPU server or a multi-node request matches the workload.
Step 1: Write down the… See the full description on the dataset page: https://huggingface.co/datasets/bhkcloud11/gpu-server-rental-cost-planning-worksheet.gpu-demand-chip-supply-coherence-risk-v0.1What this repo is for
Detect when GPU demand growth
outpaces chip supply reality.
Flags
lead times extend as demand rises
allocations tighten before deployment stalls
price spikes without demand signal
supply response looks implausible under high demand
mobile_gpu_datasetgpu_specNECL_GPUs