The SWE-rebench leaderboard has been updated with a new multilingual slice that evaluates software engineering tasks across five programming languages: Go, Java, Python, Rust, and TypeScript. The update includes performance metrics for several open-weight models, with GLM-5.2 achieving the highest Pass@1 score at 62.9%. The project plans another update in 3-4 weeks focusing on models suitable for local deployment and is soliciting suggestions from the community for future evaluations. AI
IMPACT This update expands AI model evaluation to multiple programming languages, offering a more comprehensive view of coding capabilities beyond Python.
RANK_REASON The item reports on an update to a benchmark leaderboard for evaluating AI models on software engineering tasks. [lever_c_demoted from research: ic=1 ai=1.0]
- DeepSeek V4-Pro
- GLM-5.2
- Java
- MiMo V2.5 Pro
- MiniMax M3
- Python
- Qwen3.5-35B-A3B
- Qwen3.6-27B
- Qwen3.6-35B-A3B
- Rust
- SWE-rebench
- TypeScript
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