If you need a near-instant local setup, just fetch files via a basic curl request.
Follow the guidelines below to continue.
1-click setup: the app automatically fetches the large weight files.
To save you time, the system will automatically determine efficient resource allocation.
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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- Setup script for KoboldCPP executable with embedded model loading
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- Setup tool linking local models directly into open-source smart home system automated environments
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- Setup utility organizing model libraries by parameter sizes
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