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Terminal-Bench

Benchmark of hard, realistic command-line tasks that agents must complete inside a terminal sandbox.

Reference by Stanford and Laude Institute, with Harbor

IndexedApache-2.0★ 966
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About

Whether an agent can finish end-to-end tasks in a real shell environment, such as building, debugging or configuring software.

Use cases: llm-evaluation

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About the benchmark

Benchmark site
www.tbench.ai/
Current version
Terminal-Bench 4.0tbench.ai
Maintainer
Stanford and Laude Institute, with Harbortbench.ai
Launched
2025-05-19tbench.ai
Leaderboard
www.tbench.ai/

We link to the official leaderboard instead of copying scores. Benchmarks get gamed and saturate; we never use them to rank listings.

Signals

Stars
966
Forks
602
Open issues
123
Last commit
Oct 23, 2026 (8 days ago)
Last release
Aug 26, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

Version
Terminal-Bench 4.0
License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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
50+
launches shipped
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500+
media placements
founders on every account
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founders on every account

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

Terminal-Bench benchmark. Agent Mart. https://agentmart.dev/reference/terminal-bench (last updated 2026-10-24)