PostTrainBench
PostTrainBench evaluates a model's ability to autonomously post-train base models. Given pretrain-only base models, the agent must complete the full pipeline of data synthesis, training, evaluation, and iteration within a time budget, scored across downstream benchmarks such as AIME2025, BFCL, GPQA Main, GSM8K, and HumanEval.
MiniMax M3 from MiniMax currently leads the PostTrainBench leaderboard with a score of 0.371 across 1 evaluated AI models.
What PostTrainBench measures
PostTrainBench is a text benchmark that evaluates large language models on reasoning, systems, agents, and code tasks. LLM Stats tracks 1 model on this benchmark, with a maximum possible score of 1. Current average across reported models is 0.4, with the leader reaching 0.4.
Compare leaders on the best AI for reasoning, best AI for systems, best AI for agents and best AI for code leaderboards.
MiniMax M3 leads with 37.1%.
Progress Over Time
Interactive timeline showing model performance evolution on PostTrainBench
PostTrainBench Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 |  MiniMax M3New MiniMax | — | 1.0M | $0.60 / $2.40 |
FAQ
Common questions about PostTrainBench.
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