Qwen3-Coder-30B-A3B-Instruct No-Internet Version 5-Minute Setup

The fastest way to get this model running locally is via Docker.

Follow the guidelines below to continue.

The setup auto-downloads all needed files (several GBs).

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

🔗 SHA sum: 94edfe8e5160379e4cd07d59d42d82aa | Updated: 2026-06-23 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk Space: 100 GB for multi-modal model vision components Graphics: 12 GB VRAM minimum required for basic quantization

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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