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Local LLM Guide

Model

Qwen3-Coder 480B A35B Instruct

Start with a supported compressed build and short context. 384GB RAM estimate. Best use: Benchmark chasing, server side code agents, and maximum open model coding quality experiments at scale.

480B total / 35B activeCode

Best use

Benchmark chasing, server side code agents, and maximum open model coding quality experiments at scale.

Memory planning

384GB RAM estimate

Expected pace

Depends on your hardware, app, and conversation length

License

Apache-2.0; read the model’s terms before use

Who should use this model?

  • Benchmark chasing, server side code agents, and maximum open model coding quality experiments at scale.

Choose something else when

  • You want everyday local coding, affordable hardware, quick downloads, or simple laptop deployment at home.

What hardware makes sense?

The download is only part of the memory needed. Leave room for the app, the input it processes, and other open programs. For chat models, context includes the instructions, conversation, and answer. Longer context needs more memory.

CPU only
Use a smaller model for this memory limit.
8GB system memory
Use a smaller model for this memory limit.
16GB system memory
Use a smaller model for this memory limit.
32GB system memory
Use a smaller model for this memory limit.
8GB GPU memory
Use a smaller model for this memory limit.
12GB GPU memory
Use a smaller model for this memory limit.
24GB GPU memory
Use a smaller model for this memory limit.
Apple unified memory
Use a smaller model for this memory limit.

Model facts that change the decision

Parameters
480B total / 35B active
Input
Text · Code
Published context limit
262,144 tokens
Model format
safetensors · GGUF · Ollama · MLX
Suggested compression
Q4_K_M for first local attempts unless a cited runtime recommends a different default.
Typical Q4 file
276GB before runtime and context overhead
Languages
Unknown

First setup

Ollama

ollama run qwen3-coder:480b

LM Studio: Check that your installed app supports the exact model format and task before downloading it.

llama.cpp

Use the cited GGUF repository (unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF) with current llama.cpp-compatible tooling.

Conditions that change the answer

  • This should not be presented as a normal beginner local model.
  • Even quantized builds are hundreds of gigabytes before runtime overhead and context memory.
  • Ollama and LM Studio availability does not mean typical consumer hardware can run it well.
  • Full 256K context and agentic workflows require substantially more memory than the model file size.
  • Non-thinking model; it is optimized for coding and agentic tasks, not visible reasoning traces.
  • Commercial use: Permitted under Apache-2.0 terms
  • Qwen3 Coder 480B is Qwen’s flagship open coding model for agentic software engineering, but local use belongs to servers, multi GPU rigs, or huge unified memory machines rather than normal laptops for daily development work.

Read the controlling license text →