Qwen3.5-9B-MLX-4bit Using Pinokio Windows

Qwen3.5-9B-MLX-4bit Using Pinokio Windows

For the fastest local setup of this model, enabling Windows Features is best.

Make sure you implement the steps mentioned below.

An automated background process downloads all required large-scale files.

The smart installation system will instantly find the perfect configuration.

🔍 Hash-sum: c27d43f4b43dfbe12afa0189dd208bd6 | 🕓 Last update: 2026-07-06



  • CPU: multi-threading optimized for fast prompt processing
  • RAM: minimum 16 GB for stable 8B model loading
  • Disk Space:70 GB free space for full FP16 weights storage
  • GPU: modern architecture (Ada Lovelace / Ampere minimum)

The Qwen3.5-9B-MLX-4bit model delivers strong performance while maintaining a compact footprint thanks to its 9B parameters and 4-bit quantization. Its integration with the MLX framework enables optimized memory usage and accelerated inference on consumer‑grade hardware. The model supports an 8K token context window, allowing it to handle longer dialogues and complex reasoning tasks. Benchmarks show it achieves competitive perplexity scores compared to larger models, making it ideal for deployment in resource‑constrained environments. Additionally, the MLX optimizations reduce latency, providing smooth real‑time responses even on laptops and edge devices.

Parameter Value
Model Name Qwen3.5-9B-MLX-4bit
Parameters 9B
Quantization 4‑bit
Framework MLX
Context Length 8K tokens
Inference Speed >100 tokens/s (GPU)
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