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richardyoung/Qwen3-Coder-480B-GGUF
Qwen3-Coder-480B-GGUF is a text generation model from richardyoung. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
GGUF quantizations of Qwen/Qwen3-Coder-480B-A35B-Instruct for use with llama.cpp and Ollama.
Downloads · 30 days
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.gguf133 GB · 100%
From the Hugging Face model README
GGUF quantizations of Qwen/Qwen3-Coder-480B-A35B-Instruct for use with llama.cpp and Ollama.
Qwen3-Coder-480B is Alibaba's most powerful agentic coding model featuring:
| Quantization | Size | Files | RAM Required | Quality | Description |
|---|---|---|---|---|---|
| IQ2_XS | 133GB | 4 | ~150GB | Good | Extreme 2-bit, for limited RAM |
| IQ3_M | 218GB | 6 | ~240GB | Better | Balanced 3-bit (coming soon) |
| IQ4_XS | 257GB | 7 | ~280GB | Great | Recommended 4-bit (coming soon) |
# IQ2_XS quantization
ollama run richardyoung/qwen3-coder:iq2_xs "Write a Python REST API with FastAPI"
# With extended context
ollama run richardyoung/qwen3-coder:iq2_xs --num-ctx 65536 "Analyze this codebase..."
# Download all IQ2_XS shards
huggingface-cli download richardyoung/Qwen3-Coder-480B-GGUF --include "IQ2_XS/*" --local-dir .
# Run with llama.cpp
./llama-cli -m IQ2_XS/Qwen_Qwen3-Coder-480B-A35B-Instruct-IQ2_XS-00001-of-00004.gguf \
-c 32768 -n 2048 \
-p "Write a binary search tree implementation in Python"
| Quantization | Minimum RAM | Recommended |
|---|---|---|
| IQ2_XS | 150GB | 192GB unified (M2/M3/M4 Ultra) |
| IQ3_M | 240GB | 256GB+ |
| IQ4_XS | 280GB | 320GB+ |
<|im_start|>system
You are Qwen3-Coder, an expert AI coding assistant.<|im_end|>
<|im_start|>user
{user_message}<|im_end|>
<|im_start|>assistant
{assistant_response}<|im_end|>
Apache 2.0 - Free for commercial and personal use.
Built & maintained by Richard Young · DeepNeuro