Full Deployment Qwen3.6-35B-A3B-MLX-8bit on AMD/Nvidia GPU 5-Minute Setup

Full Deployment Qwen3.6-35B-A3B-MLX-8bit on AMD/Nvidia GPU 5-Minute Setup

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

Please adhere to the deployment steps listed below.

The setup auto-streams the model assets (expect a multi-GB download).

During setup, the script automatically determines and applies the best settings.

🔧 Digest: 1ceb4e892066a602f7dbc3a863c65ade • 🕒 Updated: 2026-06-25



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: high-speed DDR5 memory preferred for CPU offloading
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

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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