How to Install Qwen3-Coder-30B-A3B-Instruct-FP8 Locally via Ollama 2 For Low VRAM (6GB/8GB)

Deploying this model locally is quickest when done via a simple curl command.

Check out the detailed setup guide below to begin.

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

You don’t need to tweak anything; the installer picks the highest performing setup.

🔗 SHA sum: d59c9342409db269b75f96982f8412fc | Updated: 2026-06-30 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: 64 GB to avoid OOM crashes on large contexts Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphics: CUDA Compute Capability 8.0+ required for flash-attention

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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