Benchmark

PostTrainBench

Measures: A CLI agent gets a small base model (1 to 4B parameters), one H100 and 10 hours to improve it by post-training; the score averages the result over four base models and seven evaluations.

Maintainer
Rank et al. (ELLIS Institute Tübingen, Max Planck Institute for Intelligent Systems, University of Tübingen)
Introduced
2026
Status
Active
Saturation
Headroom
Typical provenance
Independent
In scoring set
No

Official leaderboard

Every result we hold, whoever ran it. Only independent and third-party rows count towards a score.

Leaderboard
ModelAverage scoreProvenanceSourceEvaluated
GPT-5.4
OpenAI · High effort
19.0%Source not statedEpoch AI via Epoch AI—
Gemini 3.1 Pro22.0%Source not statedEpoch AI via Epoch AI—
Grok 4.5
SpaceXAI (xAI) · High effort
23.4%Source not statedEpoch AI via Epoch AI—
GPT-5.5
OpenAI · Xhigh effort
27.2%Source not statedEpoch AI via Epoch AI—
Claude Opus 4.7
Anthropic · Xhigh effort
28.6%Source not statedEpoch AI via Epoch AI—
GLM-5.2
Z.ai (Zhipu AI) · Max effort
31.7%Source not statedEpoch AI via Epoch AI—
Kimi K3
Moonshot AI · Unknown effort
32.0%Source not statedEpoch AI via Epoch AI—
Claude Opus 4.8
Anthropic · Max effort
32.9%Source not statedEpoch AI via Epoch AI—
Claude Opus 4.8
Anthropic · High effort
33.8%Source not statedEpoch AI via Epoch AI—
Claude Opus 5
Anthropic · Unknown effort
35.0%Source not statedEpoch AI via Epoch AI—
GPT-5.6 Sol
OpenAI · Max effort
36.2%Source not statedEpoch AI via Epoch AI—
Claude Fable 5
Anthropic · Max effort
41.8%Source not statedEpoch AI via Epoch AI—
  • Epoch AI, 'Capabilities & benchmarking', epoch.ai/benchmarks, CC BY 4.0.

Sources