Evals for AI research agents

Leaderboards for benchmarks that measure whether agents can do real research work, combining official results with scores model makers have reported.

PostTrainBench

Can LLM agents post-train a base model? Each agent gets one H100 and 10 hours to improve four small base models across held-out benchmarks.

Last synced

  • Google
  • Anthropic
  • OpenAI
  • xAI
  • Moonshot
  • Z.ai
  • Other makers
PostTrainBench
AgentWeighted scoreAIME 2025Arena HardGPQA MainGSM8KHealthBenchHumanEval
Official instruct models, Reference48.4129.270.236.287.043.371.5
Fable 5.1, Claude Code, Max44.65 ± 2.7213.287.129.2 (Includes fallback scores from Opus 5)86.449.663.0
Fable 5.2, Claude Code, Max44.64 ± 1.1613.7 (Includes fallback scores from Opus 5.5)73.7 (Includes fallback scores from Opus 5.5)33.8 (Includes fallback scores from Opus 5.5)85.251.6 (Includes fallback scores from Opus 5.5)61.3
Opus 5.5, Claude Code, Max43.80 ± 3.0011.088.129.572.353.065.3
GPT-6 Astra, Codex CLI, Max41.88 ± 0.7611.863.633.585.940.369.2
Locus, Intology · Opus 541.66 ± 0.829.466.333.182.944.366.6
Gemini 4 Carbon, OpenCode, High40.98 ± 1.6712.665.531.485.645.354.0
Gemini 4 Argon, OpenCode, High40.44 ± 0.719.265.530.883.340.967.5
GPT-6.1 Sol, Codex CLI, Max38.79 ± 0.3610.352.832.786.839.956.3
Fable 5, Claude Code, Max37.27 ± 1.6511.454.128.5 (Includes fallback scores from Opus 4.8 Max)83.840.150.8
GLM 5.3 Flash, Claude Code, Max36.79 ± 0.1110.963.327.383.337.647.1
Opus 5, Claude Code35.66 ± 2.629.753.431.180.538.740.7
GLM 5.3, Claude Code, Max34.52 ± 3.3910.238.928.383.238.845.6
Kimi K3, Claude Code31.48 ± 0.6310.634.425.576.329.550.1
GPT-5.6 Sol, Codex CLI, Max31.01 ± 0.206.326.429.669.027.463.3
Opus 4.8, Claude Code, Max31.00 ± 3.007.436.128.569.231.747.5
Opus 4.8, Claude Code, High30.66 ± 3.048.445.820.969.632.448.6
GLM 5.2, Claude Code, Max30.40 ± 1.467.427.030.272.626.552.2
Opus 4.7, Claude Code, xHigh24.34 ± 1.635.919.627.261.017.840.7
Muse Wonder, OpenCode, xHigh24.19 ± 1.1412.324.326.170.613.024.0
GPT-5.5, Codex CLI, xHigh23.87 ± 0.483.812.030.650.719.247.0
Grok 4.5, Cursor CLI, High22.62 ± 0.949.611.026.865.010.635.1
Gemini 3.1 Pro, OpenCode18.11 ± 1.684.07.417.845.316.237.3
GPT-5.4, Codex CLI, High17.76 ± 1.800.49.626.347.512.326.7
Base models (zero-shot), Reference8.011.71.38.520.49.512.8

Official scores come from the PostTrainBench leaderboard and refresh hourly. Entries marked Reported come from the model maker’s own announcement, may use a different setup, and are replaced once the official leaderboard publishes its own run. Scores are not comparable across versions.