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Terminal-Bench 4.0

Terminal-agent tasks · 17 models · source Stanford / Laude Institute · updated 2026-10

AA Intelligence Index v5GPQA DiamondLiveBench DesignVals IndexAA Intelligence Index v4.3.2
What this benchmark measures

Software-engineering tasks inside a real container: install the environment, run the tests, read the errors, fix the code. Every model runs the same mini-SWE-agent scaffold so scaffolding is not a variable.

Why it gets its own table

This is the best available predictor of whether you can hand over a repository and walk away. The spread is enormous: 67% at the top, 20-40% in the middle, 1-2% for light open models.

Full ranking

#ModelScoreVs. bestInput $Output $Type
1 Kimi K3.1 Pro Open weightsMoonshot AI 67.2 Best overall $2.00 $10.00 Open weights
2 Gemini 4 CarbonGoogle 65.2 97% $4.00 $20.00
3 Claude Sonnet 5.5Anthropic 63.6 95% $2.00 $10.00
4 Claude Opus 5.5Anthropic 59.6 89% $4.00 $20.00
5 GPT-6 AstraOpenAI 59.1 88% $10.00 $50.00
6 Gemini 4 ArgonGoogle 57.1 85% $2.00 $10.00
7 GPT-6.1 SolOpenAI 56.1 83% $2.00 $10.00
8 GPT-6.1 TerraOpenAI 55.6 83% $1.00 $5.00
9 Claude Fable 5.1Anthropic 52.0 77% $10.00 $50.00
10 GLM-5.3 Open weightsZ.ai 41.9 62% $1.40 $4.40 Open weights
11 Qwen3.8 MaxAlibaba Qwen 38.9 58% $2.00 $6.00
12 MiMo-V2.6 Pro Open weightsXiaomi 31.3 47% $0.35 $1.40 Open weights
13 Grok 4.7xAI 25.8 38% $2.00 $6.00
14 DeepSeek V4.1 Flash Open weightsDeepSeek 19.7 29% $0.30 $1.20 Open weights
15 Kimi K3 Open weightsMoonshot AI 17.2 26% $3.00 $15.00 Open weights
16 DeepSeek V4 Pro Open weightsDeepSeek 14.1 21% $1.32 $3.96 Open weights
17 MiniMax M3 Open weightsMiniMax 1.0 1% $0.30 $1.20 Open weights