MLE-bench
75 Kaggle competitions turned into offline tasks for testing machine learning engineering agents.
Reference by OpenAI
Chalk Labs
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About
Use cases: llm-evaluation
Reviews
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About the benchmark
- Benchmark site
- github.com/openai/mle-bench
- Maintainer
- OpenAIarxiv.org
- Launched
- 2024-10arxiv.org
- Leaderboard
- github.com/openai/mle-bench#leaderboard
We link to the official leaderboard instead of copying scores. Benchmarks get gamed and saturate; we never use them to rank listings.
Signals
- Stars
- 1,782
- Forks
- 263
- Open issues
- 4
- Last commit
- Apr 24, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- License unknown
- Repository
- github.com/openai/mle-bench
- Website
- github.com/openai/mle-bench
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
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Done for you
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Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
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Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
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- launches shipped
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- 500+
- media placements
- founders on every account
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Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
MLE-bench benchmark. Agent Mart. https://agentmart.dev/reference/mle-bench (last updated 2026-10-24)