PostTrainBenchBrowse 284 families

PostTrainBench

Can the model complete substantial programming work under this benchmark's agent setup?

Version / measure
Domain
Coding
Ranked models
8
Reported values
11
Reports
2 · lab
Direction
Higher is better
Status
Version not specified

Rankings

Best reported score per model across effort settings

8 models
#ModelBest settingScore
1Claude Fable 5Anthropicmaxcost n/a1 value · Jul 17 · source41.4%
2Claude Opus 4.8Anthropicreportedcost n/a2 values · Jun 16 · source37.2%
3Kimi K3Moonshot AIOWmaxcost n/a1 value · Jul 17 · source36.6%
4GPT-5.6 SolOpenAImaxcost n/a1 value · Jul 17 · source34.6%
5GLM-5.2Z.aiOWmaxcost n/a2 values · Jul 17 · source34.3%
6GPT-5.5OpenAIxhighcost n/a2 values · Jul 17 · source28.4%
7Gemini 3.1 ProGooglereportedcost n/a1 value · Jun 16 · source21.6%
8GLM-5.1Z.aiOWreportedcost n/a1 value · Jun 16 · source20.1%

Effort curve

Score vs. reported cost. Lines connect complete sweeps only.

0 values
No cost-linked effort sweep for this version.
Definition and comparison boundarypublic methodology

Can the model complete substantial programming work under this benchmark's agent setup?

Software implementation, debugging, or repository work under the published evaluation protocol. Higher is better. The value is the percentage reported in this lab's table.

Harness, tools, prompts, attempt count, and benchmark version can materially change the result. Compare within one reporting context.

Claude Code harness.

Method / source ↗