Deploying this model locally is quickest when done via a simple curl command.
Execute the commands and steps outlined below.
All large files and heavy weights are downloaded automatically by the script.
The initial setup handles the heavy lifting, fine-tuning the environment for your device.
The Qwen3.5-9B-MLX-4bit model delivers strong performance while maintaining a compact footprint thanks to its 9B parameters y 4-bit quantization. Its integration with the MLX framework enables optimized memory usage y 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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