The MoE architecture adopted by Qwen3-Coder-480B realizes the balance between parameter size and computational efficiency, and its 3.5 billion activation parameters are designed so that the memory consumption of a single inference is only 15% of the dense model.Benchmark tests show that its code generation speed is 4.2 times faster than that of the traditional dense model under the same hardware conditions, which is especially suitable for real-time programming assistance scenarios. The architecture assigns specialized code knowledge (e.g. concurrent programming, GPU optimization) to different expert modules through a dynamic routing algorithm, which improves the generation quality of domain-specific code by 371 TP3T. In real-world deployments, the 8bit-quantized version of 7B achieves a generation speed of 200 token/s on consumer GPUs (e.g. RTX 4090), which fully meets the IDE plug-in's Performance Requirements
This answer comes from the articleQwen3-Coder: open source code generation and intelligent programming assistantThe
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