Using the Windows Package Manager is the quickest way to trigger the setup.

Make sure you implement the steps mentioned below.

The installer automatically pulls the model (could be multiple GBs).

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

🧩 Hash sum → 2356007909c72786a2c81d5b246a81d7 — Update date: 2026-07-04 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: 48 GB needed to prevent memory swapping to disk Disk: high-speed SSD 120 GB to cache model layers Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

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.

• Setup tool installing LocalAI server container with core configurations
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• Script automating local installation of Open-WebUI with Docker Desktop
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• Script fetching optimized Qwen model variants for terminal-based chat
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