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SWE-Bench Multilingual benchmark
AI model leaderboard for the SWE-Bench Multilingual benchmark. Compare how large language models score on SWE-Bench Multilingual, see the full ranking, and understand what this AI benchmark measures. DeepSeek-V3.2 currently leads with 70.2. Multilingual extension of SWE-Bench — real GitHub issues across Python, Java, JavaScript, Go, etc.
Leaderboard
| # | Model | Organization | Score | Variant | Source |
|---|---|---|---|---|---|
| #1 | DeepSeek-V3.2 | DeepSeek | 70.2 | cited-devstral-readme | official ↗ |
| #2 | DeepSeek-V3.2 | DeepSeek | 70.2 | thinking | official ↗ |
| #3 | Claude Sonnet 4.5 | Anthropic | 68 | cited-devstral-readme | official ↗ |
| #4 | Claude Sonnet 4.5 | Anthropic | 68 | cited-deepseek-v3-2 | official ↗ |
| #5 | Devstral 2 | Mistral AI | 61.3 | from-hf-readme | official ↗ |
| #6 | Kimi K2 Thinking | Moonshot | 61.1 | thinking-w-tools | official ↗ |
| #7 | Kimi K2 Thinking | Moonshot | 61.1 | cited-devstral-readme | official ↗ |
| #8 | Kimi K2 Thinking | Moonshot | 61.1 | thinking-cited-deepseek-v3-2 | official ↗ |
| #9 | DeepSeek-V3.2-Exp | DeepSeek | 57.9 | from-hf-readme | official ↗ |
| #10 | MiniMax-M2 | MiniMax | 56.5 | cited-deepseek-v3-2 | official ↗ |
| #11 | MiniMax-M2 | MiniMax | 56.5 | cited-devstral-readme | official ↗ |
| #12 | Kimi K2 | Moonshot | 55.9 | k2-0905-w-tools-cited-k2-thinking | official ↗ |
| #13 | Devstral Small 2 | Mistral AI | 55.7 | from-hf-readme | official ↗ |
| #14 | GPT-5 | OpenAI | 55.3 | cited-deepseek-v3-2 | official ↗ |
Frequently asked questions about SWE-Bench Multilingual
What is the SWE-Bench Multilingual benchmark?
Multilingual extension of SWE-Bench — real GitHub issues across Python, Java, JavaScript, Go, etc.
How is the SWE-Bench Multilingual benchmark scored?
SWE-Bench Multilingual is scored using the resolution_rate metric, where a higher score is better. GenAIList aggregates reported scores from model providers and papers into a single ranked leaderboard.
Which AI model scores highest on SWE-Bench Multilingual?
As of the latest reported scores on GenAIList, DeepSeek-V3.2 achieves the highest result on SWE-Bench Multilingual with a score of 70.2.
Is a higher SWE-Bench Multilingual score better?
Yes. On SWE-Bench Multilingual a higher score indicates better performance, so models near the top of the leaderboard are the strongest.