Launch Qwen3.6-35B-A3B-MLX-8bit on Your PC Local Guide

To install this model locally in the shortest time, opt for Docker.

Just follow the guidelines provided below.

Then, run the build command to initialize the Docker container.

🛠 Hash code: 85f669786447e2bf03ff18f880c4fa14 — Last modification: 2026-06-25



  • Processor: Intel i5 or AMD Ryzen 5 for basic 7B models
  • RAM: 32 GB or higher for smooth 32k context lengths
  • Disk Space:70 GB free space for full FP16 weights storage
  • Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

The Qwen3.6-35B-A3B-MLX-8bit model delivers state‑of‑the‑art performance while maintaining a compact footprint thanks to its 8‑bit quantization. With 35 billion parameters and optimized architecture, it achieves high accuracy on a wide range of NLP tasks. Built on the MLX framework, the model benefits from enhanced hardware compatibility and reduced memory usage. Its inference latency is notably low, enabling real‑time applications in production environments. The following table summarizes the key technical specifications that differentiate this model from earlier versions. Users can expect consistent results across diverse benchmarks, making it a reliable choice for both research and commercial deployment.

Parameter Value
Model Name Qwen3.6-35B-A3B-MLX-8bit
Parameters 35B
Quantization 8-bit
Framework MLX
Context Length 8K tokens
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