Alibaba
Qwen3-Coder 30B A3B Instruct
最先端
1.9Mダウンロード1.1KいいねJul 2025公開日256K トークンコンテキストApache 2.0ライセンス100 卓越品質
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.
はじめに
— コピー&ペーストでローカル実行Copy-paste commands to run Qwen3-Coder 30B A3B Instruct on your machine.
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
関連モデル
おすすめ
最適なハードウェア
Qwen3-Coder 30B A3B Instructのおすすめ
このモデルを実行
量子化オプション
量子化レベル別VRAM推定値
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—
ハードウェア互換性
全ハードウェアの適合度推定
Computing compatibility...
メモリ内訳
Reference: RTX 2060 6GB
Weights18.6 GB
KV Cache1.5 GB
Runtime1.2 GB
Headroom0.6 GB
よくある質問
FAQ — Qwen3-Coder 30B A3B Instruct
関連項目