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An OpenAI-compatible multimodal Qwen server optimized for Apple Silicon, supporting Qwen3-Omni and Qwen3.6-27B models, with memory budget management, multimodal input, and tool calling capabilities.
Section 01
An OpenAI-compatible multimodal Qwen server optimized for Apple Silicon, supporting Qwen3-Omni and Qwen3.6-27B models, with memory budget management, multimodal input, and tool calling capabilities.
Section 02
Section 03
With the rise of Apple Silicon chips (M1/M2/M3 series) in the AI inference field, more and more developers want to run large language models and multimodal models efficiently on Mac devices. However, existing inference frameworks are often not sufficiently optimized for Apple Silicon or lack full support for multimodal capabilities. The mlx-vlm-server project was created to solve this problem; it is based on Apple's MLX framework and provides a multimodal model service optimized specifically for Apple Silicon.
Section 04
mlx-vlm-server implements an interface compatible with the OpenAI API, which means:
Section 05
The project supports true multimodal input and output:
Input Support:
Output Support:
Section 06
The project runs two powerful Qwen models simultaneously in one process:
This design allows the models to work collaboratively and leverage their respective strengths.
Section 07
Addressing the memory constraints of Apple Silicon devices, the project implements intelligent memory management:
Section 08
MLX is a framework designed by Apple specifically for machine learning, with the following advantages:
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