Qwen3.5-9B-GGUF Windows 10 Quantized GGUF 5-Minute Setup

If you want the fastest local installation for this model, use Docker.

Refer to the instructions below to proceed.

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

The installer will automatically analyze your hardware and select the optimal configuration for your system.

🔐 Hash sum: a00494dd29a52161e97e1192c5195b8c | 📅 Last update: 2026-06-26



  • Processor: Intel i5 or AMD Ryzen 5 for basic 7B models
  • RAM: fast 5600MHz+ required to avoid memory bottlenecks
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

The Qwen3.5-9B-GGUF model represents a significant advancement in open‑source language models, offering a balanced blend of performance and efficiency for both research and commercial applications. Built on the Qwen3.5 architecture, it leverages grouped‑query attention and rotary positional embeddings to achieve faster inference while maintaining high accuracy on benchmarks. With 9 billion parameters quantized into GGUF format, the model reduces memory footprint and enables deployment on consumer‑grade hardware without sacrificing response quality. The model supports up to 8K token context windows, allowing it to handle longer dialogues and complex reasoning tasks with minimal truncation. Its integration with the GGUF format further simplifies deployment across diverse platforms, making advanced AI capabilities accessible to a broader community.

Context Length 8K tokens
Training Tokens 2 trillion
Benchmark (MMLU) 84.3%
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