Qwen3-Coder's language compatibility covers 92 programming languages ranging from mainstream industrial languages (Python/Java/C++) to rare dialects (Verilog/COBOL), and its multi-language code conversion accuracy reaches 89.7% in the IEEE standard test set. the model performs particularly well in system programming languages (Rust/Go). The model's performance in system programming languages (Rust/Go) is particularly outstanding, with the probability of generating unsafe code blocks passing the Rust compiler check reaching 931 TP3T. Practical cases show that when developers use the model for Python to CUDA conversion, the adoption rate of performance optimization suggestions is more than 801 TP3T, which stems from the mixed-precision tokenizer technology used in the training process, which improves semantic alignment between languages by 2.3 times. alignment across languages by a factor of 2.3. For multinational teams, this feature reduces the cost of maintaining multiple codebases for 40%.
This answer comes from the articleQwen3-Coder: open source code generation and intelligent programming assistantThe
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