Qwen 3-Coder
Qwen 3 generation specialized for coding agents. 30B is competitive with 70B+ coders; 480B is a frontier-tier model.
Best for long-context code agent workflows
Sizes 30B · 480B
Context 256K
License Apache 2.0 (30B), custom (480B)
Min VRAM (default size, Q4) 18 GB
Rec VRAM 24 GB
What is Qwen 3-Coder?
Qwen 3-Coder is Alibaba's MoE open-weights language model. Released in 2025-07, it ships in 2 sizes (30B, 480B) and is licensed Apache 2.0 (30B), custom (480B). The most popular use case is long-context code agent workflows.
VRAM and hardware
The smallest 30B size needs at least 18 GB VRAM; the largest 480B needs around 18 GB.
| Size | Min VRAM (Q4_K_M) | Recommended VRAM | Tokens/sec on 3090 |
|---|---|---|---|
| 30B | 18 GB | 27 GB | ~18 tok/s |
| 480B | 280 GB | 420 GB | ~10 tok/s |
How to run Qwen 3-Coder locally
Option 1: Ollama (simplest)
ollama pull qwen-3-coder
ollama run qwen-3-coder Option 2: Mullama (production)
mullama pull qwen-3-coder
mullama run qwen-3-coder Option 3: llama.cpp (CLI)
# Download a GGUF from Hugging Face (search "qwen-3-coder gguf")
./llama-cli -m qwen-3-coder.Q4_K_M.gguf -p "Hello, AI!" Option 4: Python with Mullama or llama-cpp-python
from mullama import Model, Context
model = Model.load("qwen-3-coder.Q4_K_M.gguf", n_gpu_layers=99)
ctx = Context(model, n_ctx=4096)
print(ctx.generate("Hello, AI!", 256)) What you can build with Qwen 3-Coder
- code agents
- long-context code
- refactoring
Hardware it fits on
- Apple Silicon (8GB): 30B in MLX
- Apple Silicon (16GB): 480B in MLX
- Apple Silicon (32GB): 480B in MLX or GGUF
- Apple Silicon (64GB+): 480B in MLX
- RTX 3090 (24GB): 480B at Q4_K_M
- RTX 4090 (24GB): same as 3090, ~30% faster
- RTX 5090 (32GB): 480B at Q8_0
- 2× RTX 6000 Ada (96GB total): 480B at Q4_K_M
Related models in the Qwen family
- Qwen 2.5 — 0.5B, 1.5B, 3B, 7B, 14B, 32B, 72B · strongest 7B-32B on consumer hardware
- Qwen 2.5-Coder — 0.5B, 1.5B, 3B, 7B, 14B, 32B · best open-weight code model in 2024-2025
- Qwen 3 — 0.6B, 1.7B, 4B, 8B, 14B, 30B, 32B, 235B · best all-round local LLM in 2025-2026
- Qwen 3 VL — 2B, 4B, 8B, 30B, 32B, 235B · frontier-class vision-language with thinking
Other models you might consider
- Llama 3.1 (Meta) — 8B, general-purpose chat, agentic workflows, code
- Llama 3.2 (Meta) — 1B, low-end hardware, mobile, edge deployment
- Llama 3.2 Vision (Meta) — 11B, vision + chat on desktop GPUs
- Llama 3.3 (Meta) — 70B, best-in-class 70B for desktops
- Llama 4 (Meta) — Scout 17B (109B MoE), vision + long context (10M tokens)
- DeepSeek R1 (DeepSeek) — 1.5B, reasoning, math, step-by-step problem solving