CAPA - First-Turn Success: leaderboard

CAPA tests whether a coding assistant learns the recurring ambiguity of one user: each held-out session opens with an ambiguous coding request whose missing detail the same user has resolved the same way before, and the assistant may ask for clarification or submit code. This board is the share of sessions solved at the first turn, with no clarification asked, when the assistant is also given five resolved sessions from the same user. A simulated user answers clarifying questions and an execution-grounded judge decides whether a submission is correct.

Metric: First-turn executable success (%; share of the 300 held-out coding sessions whose first assistant turn is an accepted submission, with no clarification asked; same-user history: the model also sees the dialogue traces of five resolved sessions from the same user, whose recurring ambiguity pattern the held-out request repeats). Source: arxiv.org. Saturation forecast: Around 2028. 12 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 4.860.3#56
2GLM-5.246.7#138
3Gemini 3.5 Flash38.7#101
4Kimi K2.632.3#178
5GPT-5.531#49
6Qwen 3.7 Max29.7#145
7Qwen 3 8B23#1830
8Qwen 3.5 27B21.3#359
9GPT-5.6 Sol18.3#30
10DeepSeek V4 Pro17.7#188
11Llama 3.3 70B Instruct16#1357
12Claude Sonnet 4.614#161

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=capa-first-turn-success · How It Works · Data refreshed daily, snapshot 2026-11-13.