Qwen3-Coder-30B-A3B-Instruct

If you need a near-instant local setup, just fetch files via a basic curl request.

Execute the commands and steps outlined below.

The setup auto-streams the model assets (expect a multi-GB download).

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

🔐 Hash sum: 6ae10f0bf08e3fdf1d61d74f2c13e1e1 | 📅 Last update: 2026-06-23
  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk Space: 100 GB for multi-modal model vision components
  • 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 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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