Launch Qwen3.6-35B-A3B-MLX-8bit Using Pinokio Windows

If you want the fastest local installation for this model, use Docker.

Use the instructions provided below to complete the setup.

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

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

🛠 Hash code: 2dd346ca9833fc4acb3c81d39d5d489a — Last modification: 2026-06-26 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: minimum 16 GB for stable 8B model loading Disk: 150+ GB for high-context vector database storage Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading

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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