If you need a near-instant local setup, just fetch files via a basic curl request.

Follow the step-by-step instructions below.

Everything happens automatically, including the heavy cloud asset download.

An automated hardware sweep ensures the system will select the best tuning parameters.

🧾 Hash-sum — 4d9e4008ac85c08e967eeeeb476e7721 • 🗓 Updated on: 2026-06-26 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: 32 GB highly recommended for 26B+ GGUF models Storage: extra room for future model updates and datasets GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

The Qwen3.5-9B-MLX-4bit model delivers strong performance while maintaining a compact footprint thanks to its 9B parameters and 4-bit quantization. Its integration with the MLX framework enables optimized memory usage and accelerated inference on consumer‑grade hardware. The model supports an 8K token context window, allowing it to handle longer dialogues and complex reasoning tasks. Benchmarks show it achieves competitive perplexity scores compared to larger models, making it ideal for deployment in resource‑constrained environments. Additionally, the MLX optimizations reduce latency, providing smooth real‑time responses even on laptops and edge devices.

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