{"schema_version":"onlylabs.public_signal.v1","title":"NVIDIA Repo: NVIDIA/SOL-ExecBench","description":"NVIDIA repo signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/ce568b06-3cc5-43ee-9cb3-b14c8c2f6f95","json_url":"https://onlylabs.fyi/signals/ce568b06-3cc5-43ee-9cb3-b14c8c2f6f95/signal.json","generated_at":"2026-06-11T02:52:44.098626+00:00","org":{"slug":"nvidia","name":"NVIDIA","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/nvidia","dossier_json_url":"https://onlylabs.fyi/labs/nvidia/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/ce568b06-3cc5-43ee-9cb3-b14c8c2f6f95","signal_json":"https://onlylabs.fyi/signals/ce568b06-3cc5-43ee-9cb3-b14c8c2f6f95/signal.json","source":"https://github.com/NVIDIA/SOL-ExecBench","lab_dossier":"https://onlylabs.fyi/labs/nvidia","lab_dossier_json":"https://onlylabs.fyi/labs/nvidia/dossier.json","analysis":"https://onlylabs.fyi/analysis/nvidia","analysis_json":"https://onlylabs.fyi/analysis/nvidia/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/nvidia/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":null,"topic_signals_json":null,"topic_feed":null,"data_business":{"radar":"https://onlylabs.fyi/data-radar","radar_json":"https://onlylabs.fyi/data-radar.json","opportunities":"https://onlylabs.fyi/opportunities","opportunities_json":"https://onlylabs.fyi/opportunities.json","lanes":[{"key":"evals","label":"Evals and quality","url":"https://onlylabs.fyi/data-radar/evals","json_url":"https://onlylabs.fyi/data-radar/evals/signals.json"}]}},"answer_pack":{"answer":"NVIDIA published NVIDIA/SOL-ExecBench (Python). 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Kernels are: * Checked for various forms of reward hacking * Tested against a reference solution for numerical correctness * Timed under reproducible conditions Leaderboard submissions are ranked based on [SOL-Score](/src/sol_execbench/sol_score.py): a metric that grades custom kernel performance based on the..."},"evidence_pages":[{"url":"https://github.com/NVIDIA/SOL-ExecBench","final_url":"https://github.com/NVIDIA/SOL-ExecBench","title":"NVIDIA/SOL-ExecBench repository metadata","http_status":200,"content_type":"application/json","capture_method":"plain","fetched_at":"2026-06-11T02:52:44.098626+00:00","bytes":14862,"raw_path":"1c51f961a2a4c39af1956ca547281496c1647b0314970176c1fa871e47ed8841.json","content_hash":"f18a3adfa0f2a5b5948a0e35d228238d7d65d3fa24c3ceb0bb884f8b0c988851","excerpt_chars":1200,"truncated":true,"excerpt":"NVIDIA/SOL-ExecBench Description: A benchmark of real-world DL kernel problems Language: Python License: Apache-2.0 Stars: 219 Forks: 23 Open issues: 2 Created: 2026-03-04T23:59:22Z Pushed: 2026-05-28T19:41:55Z Default branch: main Fork: no Archived: no README: SOL ExecBench <div align=\"center\" id=\"top\"> [![Docs](https://img.shields.io/badge/docs-latest-brightgreen.svg)](/docs/) [![License: Apache-2.0](https://img.shields.io/badge/License-Apache--2.0-blue.svg)](LICENSE) [HuggingFace Dataset](https://huggingface.co/datasets/nvidia/SOL-ExecBench) | [Leaderboard](https://research.nvidia.com/benchmarks/sol-execbench) | [Technical Report](https://arxiv.org/abs/2603.19173) </div> **Speed-Of-Light ExecBench** is a rigorous GPU kernel evaluation and benchmarking framework built to benchmark AI-generated kernel solutions written with the variety of DSLs that NVIDIA hardware supports. 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