benchgap
Calibration

Vals SWE-bench → PostTrainBench v1.1

PostTrainBench v1.1 is estimated from Vals SWE-bench with a inverse Michaelis–Menten curve fitted on 9 models measured on both: y = 0.38080·(x − 0.0000) / (0.0000 + 2.0000 − x), R² = 0.61, cross-validated error 3.3 pp. It is used for 48 estimates.

Estimated modelVals SWE-benchPostTrainBench v1.1Source
DeepSeek V4 Pro 081396.4%35.4%estimated ± 3.3 pp, high confidence
Grok 4.695.6%34.9%estimated ± 3.3 pp, high confidence
GLM-5.395.4%34.7%estimated ± 3.3 pp, high confidence
GPT-5.6 Terra95.4%34.7%estimated ± 3.3 pp, high confidence
Claude Fable 595.0%34.5%estimated ± 3.3 pp, high confidence
GPT-5.6 Luna93.0%33.1%estimated ± 3.3 pp, high confidence
GLM-5.3-Flash92.0%32.4%estimated ± 3.3 pp, high confidence
DeepSeek V4 Flash 073188.8%30.4%estimated ± 3.3 pp, high confidence
Muse Spark 1.286.6%29.1%estimated ± 3.3 pp, high confidence
Qwen3.8-27B86.0%28.7%estimated ± 3.3 pp, high confidence
Qwen3.8 Max85.6%28.5%estimated ± 3.3 pp, high confidence
Inkling-Small82.2%26.6%estimated ± 3.3 pp, high confidence
Muse Spark 1.182.0%26.5%estimated ± 3.3 pp, high confidence
Gemini 3.7 Flash80.8%25.8%estimated ± 3.3 pp, high confidence
Gemini 3.8 Flash80.0%25.4%estimated ± 3.3 pp, high confidence
Claude Sonnet 579.6%25.2%estimated ± 3.3 pp, high confidence
Composer 2.579.6%25.2%estimated ± 3.3 pp, high confidence
Gemini 3.6 Flash79.6%25.2%estimated ± 3.3 pp, high confidence
Gemini 3.5 Flash78.8%24.8%estimated ± 3.3 pp, high confidence
Kimi K2.7 Code78.2%24.4%estimated ± 3.3 pp, medium confidence
GPT-5.3 Codex78.0%24.3%estimated ± 3.3 pp, medium confidence
Inkling77.6%24.1%estimated ± 3.3 pp, medium confidence
Claude Sonnet 4.677.4%24.0%estimated ± 3.3 pp, medium confidence
GLM-5.176.4%23.5%estimated ± 3.3 pp, medium confidence
Kimi K2.676.2%23.4%estimated ± 3.3 pp, medium confidence
Gemini 3.5 Flash-Lite75.0%22.8%estimated ± 3.3 pp, medium confidence
Gemini 3 Flash75.0%22.8%estimated ± 3.3 pp, medium confidence
MiniMax M375.0%22.8%estimated ± 3.3 pp, medium confidence
Muse Spark74.4%22.6%estimated ± 3.3 pp, medium confidence
MiMo-V2.5-Pro74.0%22.4%estimated ± 3.3 pp, medium confidence
MiniMax M2.773.8%22.3%estimated ± 3.3 pp, medium confidence
Qwen3.6 Plus73.4%22.1%estimated ± 3.3 pp, medium confidence
GPT-5.4 mini73.0%21.9%estimated ± 3.3 pp, medium confidence
Qwen 3.6 Max (preview)72.8%21.8%estimated ± 3.3 pp, medium confidence
GPT-5.2-Codex72.4%21.6%estimated ± 3.3 pp, medium confidence
Grok 4.2072.2%21.5%estimated ± 3.3 pp, medium confidence
Grok 4.371.4%21.1%estimated ± 3.3 pp, medium confidence
MiMo-V2.571.0%21.0%estimated ± 3.3 pp, medium confidence
Qwen3.6-27B70.0%20.5%estimated ± 3.3 pp, medium confidence
GPT-5.4 nano69.8%20.4%estimated ± 3.3 pp, medium confidence
GLM-4.769.4%20.2%estimated ± 3.3 pp, medium confidence
Nemotron 3 Ultra69.0%20.1%estimated ± 3.3 pp, medium confidence
Qwen3.7 Max68.8%20.0%estimated ± 3.3 pp, medium confidence
Claude Haiku 4.566.6%19.0%estimated ± 3.3 pp, medium confidence
Mistral Medium 3.5 128B66.4%18.9%estimated ± 3.3 pp, medium confidence
Ling 3.0 Flash65.2%18.4%estimated ± 3.3 pp, medium confidence
Qwen3.5 Flash64.4%18.1%estimated ± 3.3 pp, medium confidence
Gemini 3.1 Flash-Lite62.8%17.4%estimated ± 3.3 pp, medium confidence

Fitted on

ModelVals SWE-benchPostTrainBench v1.1
Claude Opus 4.782.0%28.6%
Claude Opus 4.888.6%32.9%
Claude Opus 597.0%35.0%
Gemini 3.1 Pro78.8%22.0%
GLM-5.282.8%31.7%
GPT-5.582.6%27.2%
GPT-5.6 Sol96.2%36.2%
Grok 4.586.6%23.5%
Kimi K393.4%32.0%