Alibaba
Qwen3-Coder 30B A3B Instruct
Frontier
1.9MDownloads1.1KCurtidasJul 2025Publicado256K tokensContextoApache 2.0Licença100 ExcepcionalQualidade
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.
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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
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Opções de quantização
Estimativas de VRAM por nível de quantização
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—
Compatibilidade de hardware
Estimativas de compatibilidade para todo o hardware
Computing compatibility...
Detalhamento de memória
Reference: RTX 2060 6GB
Weights18.6 GB
KV Cache1.5 GB
Runtime1.2 GB
Headroom0.6 GB
Perguntas frequentes
FAQ — Qwen3-Coder 30B A3B Instruct
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