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
SWE-bench Multilingual
Per-language resolution rates differ widely, so an average hides which languages the model actually handles.
Evaluation context and evidence
- Source
- Model reports
- Publisher
- Not recorded
- Benchmark release
- 2025-04-22
- Collected
- Not recorded
- Modality
- Not recorded
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.
Original sources
Reported results 7
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 | 69.8 | percent | non-think, resolved | 2026-04-22 · document_publication | DeepSeek-V4-Pro |
| DeepSeek-V4-Pro | 74.1 | percent | think high, resolved | 2026-04-22 · document_publication | DeepSeek-V4-Pro |
| DeepSeek-V4-Pro | 76.2 | percent | think max, resolved | 2026-04-22 · document_publication | DeepSeek-V4-Pro |
| DeepSeek-V4-Flash | 73.3 | percent | think max, resolved | 2026-06-25 · document_publication | DeepSeek-V4 |
| Qwen3.5-397B-A17B | 69.3 | percent | thinking (temp 0.6, top_p 0.95, top_k 20) | 2026-02-16 · document_publication | Qwen3.5-397B-A17B |
| Hy4 preview | 82.9 | percent | as printed in the report's benchmark table | 2026-08-28 · document_publication | Hy4 preview |
| GLM-5 | 73.3 | percent | OpenHands, tailored instruction prompt, temp 0.7, top_p 0.95, 200K context | 2026-02-11 · document_publication | GLM-5 |