Fangcun DeepSeek 1017 Report - RE-Bench Embedding log loss above1.5: 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. Embedding repair, source native natural-log loss offset. Lower is better; no transformation or empirical-axis bounds. Metric: ln (loss - 1.5).
Metric: ln(loss - 1.5). Source: arxiv.org. Saturation forecast: Around August 2028. 7 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5.6 Sol (Max) | 0.05 | #19 (GPT-5.6 Sol) |
| 2 | GPT-6 Astra (Max) | 0.05 | #3 (GPT-6 Astra) |
| 3 | DeepSeek V4 Pro (Max) | 0.06 | #109 (DeepSeek V4 Pro) |
| 4 | DeepSeek V4 Flash (Max) | 0.56 | #147 (DeepSeek V4 Flash) |
| 5 | DeepSeek V4.1 Flash (1017) (Max) | 0.83 | #25 (DeepSeek V4.1 Flash (1017)) |
| 6 | DeepSeek V4.1 Flash (Max) | 1.3 | #36 (DeepSeek V4.1 Flash) |
| 7 | Gemini 3.8 Flash | 2.2 | #24 |
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-re-bench-embedding-log-loss-above1-5 · How It Works · Data refreshed daily, snapshot 2026-10-28.