Running this model locally is fastest when deployed through Docker.
Please follow the instructions listed below to get started.
Hands-free setup: the system self-downloads the heavy model files.
The smart installation system will instantly find the perfect configuration for your specific hardware.
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) |
- Adjustable damage multiplier trainer script with programmable toggle keys
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- Corrupted game asset bypass patch preventing random world-load crashes
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- Console port control scheme layout remapper for mouse and keyboard
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