Alibaba
Qwen3-Coder 30B A3B Instruct
前沿
1.9M下载量1.1K点赞Jul 2025发布日期256K tokens上下文Apache 2.0许可证100 卓越质量
Qwen3-Coder 30B A3B Instruct (30.5B parameters) requires approximately 21.9 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 3.299999952316284B active parameters, it uses less memory than its total parameter count suggests. For the best balance of quality and speed, we recommend hardware with at least 26 GB of VRAM.
快速开始
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Run
ollama run qwen3-coderQuick specs
Parameters30.5B (3.3B active)
Architecturemoe (MoE)
Context256K tokens
Modalitytext
Min RAM11.9 GB
Rec. RAM18.6 GB (Q4_K_M)
LicenseApache 2.0
FamilyQwen Coder
✓ Code✓ Reasoning
About this model
- •Significant Performance: among open models on Agentic Coding, Agentic Browser-Use, and other foundational coding tasks
- •Long-context Capabilities: with native support for 256K tokens, extendable up to 1M tokens using Yarn, optimized for repository-scale...
- •Agentic Coding: supporting for most platform such as Qwen Code, CLINE, featuring a specially designed function call format
相关模型
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最佳硬件
Qwen3-Coder 30B A3B Instruct 的最佳选择
运行此模型
量化选项
各量化级别的 VRAM 估算
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.9 GB | Low | — |
Q3_K_S | 3 | 14.9 GB | Low | — |
NVFP4 | 4 | 17.1 GB | Medium | — |
Q4_K_M | 4 | 18.6 GB | Medium | — |
Q5_K_M | 5 | 22.0 GB | High | — |
Q6_K | 6 | 25.0 GB | High | — |
Q8_0 | 8 | 32.6 GB | Very High | — |
F16 | 16 | 62.5 GB | Maximum | — |
Quality benchmarks
Qwen3-Coder 30B A3B Instruct benchmark scores
Coding
SWE-bench Verified51.6%
HumanEval+—
Aider Polyglot—
LiveCodeBench—
硬件兼容性
全部硬件的适配估算
Computing compatibility...
内存详细分析
Reference: RTX 2060 6GB
Weights18.6 GB
KV Cache1.5 GB
Runtime1.2 GB
Headroom0.6 GB
常见问题
FAQ — Qwen3-Coder 30B A3B Instruct
另请参阅