Qwen3-Coder-30B-A3B-Instruct Offline on PC Windows

Qwen3-Coder-30B-A3B-Instruct Offline on PC Windows

Running this model locally is fastest when deployed through a PowerShell script.

Please follow the instructions listed below to get started.

Be patient as the system self-retrieves massive model weights dynamically.

An automated hardware sweep ensures the system will select the best tuning parameters.

🛡️ Checksum: a75503d39620d59856de560754711a26 — ⏰ Updated on: 2026-07-03



  • Processor: 6-core 3.5 GHz minimum required
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk: high-speed SSD 120 GB to cache model layers
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

The Qwen3-Coder-30B-A3B-Instruct model is a large language model specifically optimized for code generation and software engineering tasks. It leverages an A3B architecture that balances parameter count and inference efficiency, delivering robust performance across multiple programming languages. With 30 billion parameters and a context window extending to 16 k tokens, the model can understand and generate lengthy code snippets and documentation. The model has been fine‑tuned on extensive public code repositories and instructional datasets, enabling it to follow complex coding conventions and best practices. In benchmarks such as HumanEval and MBPP, Qwen3-Coder-30B-A3B-Instruct consistently achieves top‑tier scores, often rivaling or surpassing specialized coding assistants. Below is a quick comparison of its core specifications:

Parameter Count30 B
Context Length16 k tokens
Training DataPublic code repos + instructional datasets
Primary UseCode generation & software engineering
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