Qwen3-Coder-30B-A3B-Instruct Locally via Ollama 2

To get this model running locally in no time, utilize the built-in WSL tools.

Follow the guidelines below to continue.

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

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

🗂 Hash: 312c278e1de614851ed5f3c88f63505a • Last Updated: 2026-06-26
  • Processor: next-gen chip for heavy context processing
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Storage: extra room for future model updates and datasets
  • 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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