Fangcun DeepSeek 1017 Report - PaperBench Code-Dev common seven mean: leaderboard

Fangcun independent report 2610.35671v1, Oct 4–25 2026 hosted API evaluations; source Table A.1 resolves all seven full model names. Temperature 1, top_p 0.95, maximum reasoning effort unless explicitly overridden; GLM 5.3 rubric judge. API/format failures excluded according to source; not locally deployed weights or uncensored variants. PaperBench Code-Dev, fixed 1 hour per paper to implement full repository; hierarchical implementation checklist, not end-to-end research reproduction. Printed one-decimal per-paper scores retained; missing execution/timeout cells omitted. Common aggregate uses only 7 papers valid for all models, not all 10. Metric: Implementation checklist (%).

Metric: Implementation checklist (%). Source: arxiv.org. Saturation forecast: Around January 2027. 7 models tracked.

Top models

#ModelScoreOverall rank
1GPT-6 Astra (Max)98.97#3 (GPT-6 Astra)
2GPT-5.6 Sol (Max)96.65#19 (GPT-5.6 Sol)
3DeepSeek V4.1 Flash (1017) (Max)96.45#25 (DeepSeek V4.1 Flash (1017))
4DeepSeek V4.1 Flash (Max)94.96#36 (DeepSeek V4.1 Flash)
5DeepSeek V4 Pro (Max)92.03#109 (DeepSeek V4 Pro)
6Gemini 3.8 Flash88.56#24
7DeepSeek V4 Flash (Max)57.64#147 (DeepSeek V4 Flash)

No result here: #2 Claude Opus 5.5, #6 GPT-6.1 Sol, #8 Gemini 4 Argon.

Interactive version: theaggregate.ai/benchmark?slug=fangcun-deepseek-1017-report-paperbench-code-dev-common-seven-mean · How It Works · Data refreshed daily, snapshot 2026-10-28.