Qwen3-Coder-30B-A3B-Instruct-FP8

Checkpoints

Qwen3-Coder-30B-A3B-Instruct-FP8

For an instant local deployment, running a pre-configured shell script is ideal.

Check out the detailed setup guide below to begin.

The system automatically triggers a cloud download for all heavy weights.

Once launched, the wizard detects your specs to configure the model for maximum efficiency.

🖹 HASH-SUM: c9bd255d9548b02645cd73826e481869 | 📅 Updated on: 2026-06-29
  • Processor: 6-core 3.5 GHz minimum required
  • RAM: minimum 16 GB for stable 8B model loading
  • Disk Space: 100 GB for multi-modal model vision components
  • Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

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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  7. Setup script auto-detecting VRAM for optimal model layer splitting
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  9. Installer configuring localized web dashboard for Whisper-Large-V3 live processing
  10. Setup Qwen3-Coder-30B-A3B-Instruct-FP8 Windows 10 No-Code Guide
  11. Downloader pulling optimized code-generation weights for disconnected software systems
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