datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
rtx-5090-benchmarks
RTX 5090 LLM Benchmarks
Speed and quality benchmarks for quantized LLMs on NVIDIA RTX 5090 32GB, measured with llm-bench-rig.
Quality Benchmarks
Generative evaluation through llama-server chat completions. Replicates standard benchmark methodology using custom evaluators — no lm-evaluation-harness dependency.
Results are split by reasoning mode: comparing a thinking-on (reasoning) model's quality against a thinking-off model is apples-to-oranges, so the two groups… See the full description on the dataset page: https://huggingface.co/datasets/witcheer/rtx-5090-benchmarks.rtx-5090-benchmarks
RTX 5090 LLM Benchmarks
Speed and quality benchmarks for quantized LLMs on NVIDIA RTX 5090 32GB, measured with llm-bench-rig.
Quality Benchmarks
Generative evaluation through llama-server chat completions. Replicates standard benchmark methodology using custom evaluators — no lm-evaluation-harness dependency.
Results are split by reasoning mode: comparing a thinking-on (reasoning) model's quality against a thinking-off model is apples-to-oranges, so the two groups… See the full description on the dataset page: https://huggingface.co/datasets/omegaprime669/rtx-5090-benchmarks.seeingculture-benchmarkPaper | Project Page | Leaderboard | Explorer | Code | CMB, the video successor
Seeing Culture Benchmark (SCB)
Evaluating Visual Reasoning and Grounding in Cultural Context
The Seeing Culture Benchmark (SCB) evaluates cultural reasoning in vision-language models in two stages: i) selecting the correct visual option with multiple-choice visual question answering (VQA), and ii) segmenting the relevant cultural artifact as evidence of reasoning. Visual options in… See the full description on the dataset page: https://huggingface.co/datasets/Multimedia-SMU/seeingculture-benchmark.google-ads-benchmark-2026
Note on checksums. This README.md carries the YAML dataset-card header required by the Hugging Face hub, so its SHA-256 differs from the entry in checksums.txt; that entry refers to the canonical README in the GitHub mirror. All data files are byte-identical across mirrors. Load any table with load_dataset("ivitskiy/google-ads-benchmark-2026", "<config_name>").
Ivitskiy Ads Lab: Google Ads Panel & Benchmark Compilation 2026 (Open Research Dataset)
Two things in one package.… See the full description on the dataset page: https://huggingface.co/datasets/ivitskiy/google-ads-benchmark-2026.hungarian-riddles-benchmark
Hungarian Riddles Benchmark
Overview
This dataset is a cultural and reasoning benchmark based on 100 metaphorical, trivia-style Hungarian riddles.
The riddles are intentionally tricky and culturally grounded. They are designed to test answer correctness and reasoning quality, not only surface-level language fluency.
Dataset structure
Each row contains one riddle with reference material for evaluation.
Fields
ID – unique identifier
topic – general… See the full description on the dataset page: https://huggingface.co/datasets/boczkakaroly/hungarian-riddles-benchmark.gpt-image-edit-benchmark-results
GPT-Image-Edit — Benchmark Results
This repository contains evaluation results of GPT-Image-Edit across four standard image-editing benchmarks. All scores were computed using the official evaluation scripts provided by each benchmark.
📊 Benchmarks
Benchmark
Metrics
Folder
GEdit-EN
12 editing categories + Avg
gedit/
Complex-Edit
IF, IP, PQ, Overall
complex_edit/
ImgEdit-Full
10 editing operations + Overall
imgedit/
OmniContext
Contextual edit scores… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/gpt-image-edit-benchmark-results.controlnet-brand-fidelity-benchmark
ControlNet Preprocessor Brand Fidelity Benchmark
Study 1A — NaviTask Marketing Flyer | Phase 1 Results
Status: Phase 1 complete (6 runs). Phase 2 in progress.
Last updated: May 2026
The Enterprise Problem
The global content marketing market is valued at $524.73 billion in 2025, projected to reach $989.84 billion by 2030 at a 13.53% CAGR. Enterprise adoption of generative AI has accelerated significantly, with 65% of organisations reporting regular use of… See the full description on the dataset page: https://huggingface.co/datasets/nnanwube/controlnet-brand-fidelity-benchmark.debias_benchmark