How to Autostart Qwen3.6-35B-A3B-MLX-8bit on AMD/Nvidia GPU Uncensored Edition

How to Autostart Qwen3.6-35B-A3B-MLX-8bit on AMD/Nvidia GPU Uncensored Edition

Docker offers the quickest path to setting up this model locally.

Review and follow the instructions below.

No manual effort needed; the setup auto-ingests the large data.

The smart installation system will instantly find the perfect configuration for your specific hardware.

💾 File hash: 9d097d2b3131e9a9400b7af284115385 (Update date: 2026-06-22)



  • Processor: 6-core 3.5 GHz minimum required
  • RAM: fast 5600MHz+ required to avoid memory bottlenecks
  • Disk Space:70 GB free space for full FP16 weights storage
  • GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

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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