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
Aggregates ten heterogeneous tool suites; the per-suite spread is wide.
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 | 51.8 | percent | think max, pass@1 | 2026-04-22 · document_publication | DeepSeek-V4-Pro |
| DeepSeek-V4-Pro-0813 | 74.1 | percent | max reasoning effort, temp 1.0, top_p 0.95 | 2026-08-13 · document_publication | DeepSeek-V4-Pro-0813 |
| DeepSeek-V4-Flash | 47.8 | percent | think max, pass@1 | 2026-06-25 · document_publication | DeepSeek-V4 |
| Kimi K3 | 76.5 | percent | reasoning=max | 2026-06-13 · document_publication | Kimi K3 |
| Qwen3.5-397B-A17B | 38.3 | percent | thinking (temp 0.6, top_p 0.95, top_k 20) | 2026-02-16 · document_publication | Qwen3.5-397B-A17B |
| GLM-5.1 | 40.7 | percent | as reported | 2026-04-03 · document_publication | GLM-5.1 |
| GLM-5.2 | 48.2 | percent | official evaluation service, max_token 128K | 2026-06-16 · document_publication | GLM-5.2 |
| GLM-5 | 38.0 | percent | as reported | 2026-02-11 · document_publication | GLM-5 |