CodeGolf Bench - Python Best Percentile: leaderboard
Metric: Best percentile (0-100): for each problem, the best of the sampled Python solutions placed in the distribution of human code.golf solutions by character count (0 = worse than every human or failing, 100 = shorter than every human), averaged over problems; 115 code.golf problems (holes), solutions checked against the platform's hidden tests through its API; golfing prompt, temperature 0.2, top-p 0.95, up to 32,768 output tokens, 10 samples per problem; higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 9 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Gemini 2.5 Pro (Preview 03-25) | 68.04 |
| 2 | DeepSeek R1 | 67.09 |
| 3 | Llama 4 Maverick | 55.31 |
| 4 | DeepSeek V3 (0324) | 51.6 |
| 5 | Gemini 2.5 Flash (Preview 04-17) | 46.42 |
| 6 | DeepSeek R1 Distill Llama 70B | 42.33 |
| 7 | Qwen 3 235B A22B | 41.64 |
| 8 | Llama 4 Scout | 36.69 |
| 9 | Gemma 3 27B (IT) | 25.23 |
Interactive version: theaggregate.ai/benchmark?slug=codegolf-bench-python-best-percentile · How It Works · Data refreshed daily, snapshot 2026-10-07.