AI benchmarks and leaderboards are different things
Learn the difference between a benchmark, an evaluation run and a leaderboard, and use each to answer the right question.
Model reports
Time-sliced problem set. A score without its problem window is not comparable to any other score.
These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.
Shown in source observation order, not ranked. Dates retain the precision provided by the source.
| Model | Value | Unit | Protocol | Reported date and basis | Source |
|---|---|---|---|---|---|
| DeepSeek-R1 | 65.9 | percent | Pass@1-COT | 2025-01-22 · document_publication | DeepSeek-R1 |
| DeepSeek-V3 | 37.6 | percent | Pass@1 | 2024-12-27 · document_publication | DeepSeek-V3 |
| DeepSeek-V3 | 40.5 | percent | Pass@1-COT | 2024-12-27 · document_publication | DeepSeek-V3 |
| DeepSeek-V4-Pro | 56.8 | percent | non-think, pass@1 | 2026-04-22 · document_publication | DeepSeek-V4-Pro |
| DeepSeek-V4-Pro | 89.8 | percent | think high, pass@1 | 2026-04-22 · document_publication | DeepSeek-V4-Pro |
| DeepSeek-V4-Pro | 93.5 | percent | think max, pass@1 | 2026-04-22 · document_publication | DeepSeek-V4-Pro |
| DeepSeek-V4-Flash | 91.6 | percent | think max, pass@1 | 2026-06-25 · document_publication | DeepSeek-V4 |
| Gemini 2.5 Pro | 74.2 | percent | 1/1/2025-5/1/2025 window | 2025-06-17 · document_publication | Gemini 2.5 Pro |
| Gemma 4 (31B) | 80.0 | percent | as reported | 2026-03-11 · document_publication | Gemma 4 (31B) |
| Qwen2.5-Coder-32B-Instruct | 31.4 | percent | Pass@1 | 2024-09-18 · document_publication | Qwen2.5-Coder |
| Qwen3.5-397B-A17B | 83.6 | percent | thinking (temp 0.6, top_p 0.95, top_k 20) | 2026-02-16 · document_publication | Qwen3.5-397B-A17B |
| Qwen3-235B-A22B (Thinking) | 70.7 | percent | v5, 2024.10-2025.02 window | 2025-05-14 · document_publication | Qwen3 |