Quick Run Qwen3.6-35B-A3B-MLX-8bit on Copilot+ PC For Low VRAM (6GB/8GB) Windows

Quick Run Qwen3.6-35B-A3B-MLX-8bit on Copilot+ PC For Low VRAM (6GB/8GB) Windows

For the fastest local setup of this model, Docker is the best choice.

Follow the sequence of steps detailed below.

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

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

🛠 Hash code: fa3eb371c4bfcd5015b49d074eee5e9e — Last modification: 2026-06-25



  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: enough space for background apps and OS overhead
  • Disk Space: at least 100 GB for multiple local LLM variants
  • Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

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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