Deploy Qwen3-Coder-30B-A3B-Instruct PC with NPU Fully Jailbroken

For an instant local deployment, running a pre-configured shell script is ideal.

Refer to the action plan below to initialize the model.

1-click setup: the app automatically fetches the large weight files.

To guarantee smooth performance, the process auto-selects the best options.

📡 Hash Check: c1d94f8279176b64ef723d19833fbfe9 | 📅 Last Update: 2026-06-25
  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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 Count 30 B
Context Length 16 k tokens
Training Data Public code repos + instructional datasets
Primary Use Code generation & software engineering
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