Quick Run Qwen3-Coder-30B-A3B-Instruct Fully Jailbroken Windows

Running this model locally is fastest when deployed through Docker.

Use the instructions provided below to complete the setup.

The installer automatically pulls the model (could be multiple GBs).

The automated installation script takes care of everything by tailoring the setup perfectly to your system specs.

🧾 Hash-sum — e683658d6fe4f4e007867f21ecda0959 • 🗓 Updated on: 2026-06-23



  • Processor: high single-core performance needed for token latency
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Storage: extra room for future model updates and datasets
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

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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