Terminal-Bench 2.1
Terminal-Bench 2.1 is an updated release of the Terminal-Bench benchmark that tests AI agents' ability to operate a computer via the terminal. It evaluates how well models handle real-world, end-to-end tasks autonomously, including compiling code, training models, setting up servers, system administration, data science workflows, and security tasks.
MiniMax M3 from MiniMax currently leads the Terminal-Bench 2.1 leaderboard with a score of 0.660 across 1 evaluated AI models.
What Terminal-Bench 2.1 measures
Terminal-Bench 2.1 is a text benchmark that evaluates large language models on reasoning, tool calling, agents, and code tasks. LLM Stats tracks 1 model on this benchmark, with a maximum possible score of 1. Current average across reported models is 0.7, with the leader reaching 0.7.
Compare leaders on the best AI for reasoning, best AI for tool calling, best AI for agents and best AI for code leaderboards.
MiniMax M3 leads with 66.0%.
Progress Over Time
Interactive timeline showing model performance evolution on Terminal-Bench 2.1
Terminal-Bench 2.1 Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 |  MiniMax M3New MiniMax | — | 1.0M | $0.60 / $2.40 |
FAQ
Common questions about Terminal-Bench 2.1.
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