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Setup Qwen3-Coder-30B-A3B-Instruct-FP8 Locally via Ollama 2

By July 2, 2026No Comments

Setup Qwen3-Coder-30B-A3B-Instruct-FP8 Locally via Ollama 2

The fastest tactical way to launch this model locally is via a Docker image.

Review and follow the instructions below.

The client handles the setup, pulling gigabytes of data automatically.

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

📡 Hash Check: 1bee09aec2ec68bba8151197ac06479e | 📅 Last Update: 2026-06-26



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: enough space for background apps and OS overhead
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

Qwen3-Coder-30B-A3B-Instruct-FP8 is a large language model fine‑tuned for code generation and debugging, built on the Qwen3 architecture with 30 billion parameters and an A3B sparse attention mechanism. It leverages FP8 quantization to achieve higher inference speed while preserving accuracy across a wide range of programming tasks. The model demonstrates strong multilingual code understanding, supporting over 20 programming languages and adhering to best practices in style and documentation. In benchmarks such as HumanEval and MBPP, it consistently ranks among the top performers, delivering state‑of‑the‑art solutions with fewer tokens. A comparison table below highlights its advantages over similar models, showing superior throughput and a lower memory footprint.

Model Qwen3-Coder-30B-A3B-Instruct-FP8
Parameters 30 B
Attention A3B sparse
Quantization FP8
Supported Languages 20+ programming languages
Benchmark Score (HumanEval) 92.3%
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peter gariepy

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