Qwen3 Coder 480B A35B Instruct GGUF — Hardware Requirements & GPU Compatibility
ChatCode
860 downloads
1 likesSpecifications
- Publisher
- LM Studio Community
- Family
- Qwen
- Parameters
- 480B
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How Much VRAM Does Qwen3 Coder 480B A35B Instruct GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q3_K_L | 4.10 | 270.6 GB | — | 246.00 GB | 3-bit large quantization |
| Q4_K_M | 4.80 | 316.8 GB | — | 288.00 GB | 4-bit medium quantization — most popular sweet spot |
| Q6_K | 6.60 | 435.6 GB | — | 396.00 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 528 GB | — | 480.00 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Qwen3 Coder 480B A35B Instruct GGUF?
Q4_K_M · 316.8 GBQwen3 Coder 480B A35B Instruct GGUF (Q4_K_M) requires 316.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 412+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Qwen3 Coder 480B A35B Instruct GGUF?
Q4_K_M · 316.8 GB2 devices with unified memory can run Qwen3 Coder 480B A35B Instruct GGUF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Qwen3 Coder 480B A35B Instruct GGUF need?
Qwen3 Coder 480B A35B Instruct GGUF requires 316.8 GB of VRAM at Q4_K_M, or 528 GB at Q8_0.
VRAM = Weights + KV Cache + Overhead
Weights = 480B × 4.8 bits ÷ 8 = 288 GB
KV Cache + Overhead ≈ 28.8 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M316.8 GB- Can NVIDIA GeForce RTX 5090 run Qwen3 Coder 480B A35B Instruct GGUF?
No — Qwen3 Coder 480B A35B Instruct GGUF requires at least 270.6 GB at Q3_K_L, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Qwen3 Coder 480B A35B Instruct GGUF?
For Qwen3 Coder 480B A35B Instruct GGUF, Q4_K_M (316.8 GB) offers the best balance of quality and VRAM usage. Q6_K (435.6 GB) provides better quality if you have the VRAM. The smallest option is Q3_K_L at 270.6 GB.
VRAM requirement by quantization
Q3_K_L270.6 GB~86%Q4_K_M ★316.8 GB~89%Q6_K435.6 GB~95%Q8_0528.0 GB~99%★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen3 Coder 480B A35B Instruct GGUF on a Mac?
Qwen3 Coder 480B A35B Instruct GGUF requires at least 270.6 GB at Q3_K_L, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Qwen3 Coder 480B A35B Instruct GGUF locally?
Yes — Qwen3 Coder 480B A35B Instruct GGUF can run locally on consumer hardware. At Q4_K_M quantization it needs 316.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- What's the download size of Qwen3 Coder 480B A35B Instruct GGUF?
At Q4_K_M, the download is about 288.00 GB. The full-precision Q8_0 version is 480.00 GB. The smallest option (Q3_K_L) is 246.00 GB.
- Which GPUs can run Qwen3 Coder 480B A35B Instruct GGUF?
No single consumer GPU has enough VRAM to run Qwen3 Coder 480B A35B Instruct GGUF at Q4_K_M (316.8 GB). Multi-GPU or professional hardware is required.
- Which devices can run Qwen3 Coder 480B A35B Instruct GGUF?
2 devices with unified memory can run Qwen3 Coder 480B A35B Instruct GGUF at Q4_K_M (316.8 GB), including NVIDIA DGX A100 640GB, NVIDIA DGX H100. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.