FeatureBench - Passed Rate: leaderboard

Metric: Passed rate (%): per task, the share of executed fail-to-pass tests that pass, averaged over tasks (partial credit), on the 200-task FeatureBench Full set (feature-level development tasks traced from unit tests in 24 Python repositories: 166 extending an existing codebase and 34 implementing the feature from scratch, each with a callable interface to implement, fail-to-pass and pass-to-pass tests, internet access without browser tools and cheating checks); each model run in the named agent harness (OpenHands up to 500 steps); higher is better. Source: arxiv.org. Saturation forecast: Around January 2028. 7 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 4.545.53#79
2Gemini 3 Pro (Preview) (Low)30.08#64 (Gemini 3 Pro (Preview))
3DeepSeek V3.226.3#198
4Qwen 3 Coder 480B A35B Instruct24.55#302

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=featurebench-passed-rate · How It Works · Data refreshed daily, snapshot 2026-10-11.