LiveBench Agentic Coding

Mean score over agentic tasks in live JavaScript, TypeScript and Python repositories, where the model changes a codebase rather than writing one function. Not in LiveBench 2.0.

ModelsModels with a result.66
Top resultBest result on this benchmark.77.3%DeepSeek V4.1 Flash 1017
Top-3 spreadPoints from first to third.11.2 pts
UpdatedDate the source changed the results.25 Jun 2026

Result and cost

65 of 66 results

Results

66 results
#ModelResultThe score from the source.CostUS dollars to run one task.
01DeepSeek V4.1 Flash 1017max effortAbove fitFar above this model's index.77.3%$0.064
06Qwen3.8 Max64.6%$1.75
06Smaug Agentic64.6%$1.81
10Kimi K362.2%$1.76
12Qwen3.8-Flash-Next61.6%$0.154
13Qwen3.8-27B61.4%$0.947
14Smaug Flash61.1%$0.078
15GLM-5.360.9%$1.60
16Smaug Mini60.8%$1.07
24Grok 4.657.0%$1.79
25GLM-5.3-Flash56.8%$0.111
26Grok 4.556.5%$0.684
38GLM-5.251.8%$1.46
42GPT-5.2high effort50.3%$1.42
43GPT-5.2-Codex49.4%$0.594
51Grok Build 0.145.8%$0.258
52Kimi K2.7 Code45.7%$0.395
55Qwen3.7 Max43.6%$0.796
60Qwen3.6 Plus41.4%$1.55
61MiniMax M340.7%$0.424
63Qwen3.6-27B39.3%$0.813
66Grok 4.318.5%$0.167