MLX-VLM: Vision Language Model Inference and Fine-Tuning on Apple Silicon

Mon, 01 Jan 0001 00:00:00 +0000

Running Vision Language Models – AI systems that can simultaneously understand images and text – has traditionally required expensive NVIDIA GPUs with substantial VRAM. Apple Silicon users were largely left out of the multimodal AI revolution, forced to rely on cloud APIs or dual-machine setups. MLX-VLM by developer Blaizzy changes this equation entirely.

MLX-VLM is an open-source Python package that brings Vision Language Model inference and fine-tuning directly to Apple Silicon hardware using Apple’s MLX framework. By leveraging the unified memory architecture of M-series chips, it enables Mac users to run sophisticated multimodal models – including LLaVA, Qwen-VL, InternVL2, and PaliGemma2 – entirely on-device, with performance that often surprises even experienced practitioners.

MLX-VLM on SoloSoft

MLX-VLM: Vision Language Model Inference and Fine-Tuning on Apple Silicon