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
A dated competition, not a fixed set: each sitting is a different instrument and contamination rises once problems are published.
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-V4-Pro | 95.2 | percent | think max, pass@1 | 2026-04-22 · document_publication | DeepSeek-V4-Pro |
| DeepSeek-V4-Flash | 94.8 | percent | think max, pass@1 | 2026-06-25 · document_publication | DeepSeek-V4 |
| Qwen3.5-397B-A17B | 94.8 | percent | thinking (temp 0.6, top_p 0.95, top_k 20) | 2026-02-16 · document_publication | Qwen3.5-397B-A17B |
| Qwen3.5-397B-A17B | 92.7 | percent | thinking (temp 0.6, top_p 0.95, top_k 20) | 2026-02-16 · document_publication | Qwen3.5-397B-A17B |
| GLM-5.1 | 94.0 | percent | HMMT Nov. 2025, as reported | 2026-04-03 · document_publication | GLM-5.1 |
| GLM-5.2 | 94.4 | percent | HMMT Nov. 2025, temp 1.0, top_p 0.95, max gen 163840 tokens, GPT-5.5 (medium) judge | 2026-06-16 · document_publication | GLM-5.2 |
| GLM-5 | 96.9 | percent | HMMT Nov. 2025, temp 1.0, top_p 0.95, GPT-5.2 (medium) judge | 2026-02-11 · document_publication | GLM-5 |