Qwen3.6-35B-A3B-MLX-8bit Using Pinokio with 1M Context Step-by-Step

Deploying this model locally is quickest when done via a simple curl command.

Go through the configuration rules shown below.

The client handles the setup, pulling gigabytes of data automatically.

There is no manual tuning required; the builder deploys the best matching configuration.

📎 HASH: 7a54568560d11e0e19a706cf3bfe54b3 | Updated: 2026-06-25



  • Processor: 6-core 3.5 GHz minimum required
  • RAM: enough space for background apps and OS overhead
  • Disk Space: required: fast PCIe 4.0 drive for instant boots
  • 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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