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design

MLX-VLM: Local AI Vision

Run vision language models locally with MLX-VLM, a tool for startup founders, with 4.8k+ GitHub stars.
intermediateโฑ 30 minutes๐Ÿ’ต Free
5,161 stars669 forksPythonQuality 8/10Updated 7/15/2026100% free ยท open source
What it is

Run Apple Silicon-based vision language models locally on your Mac.

What you can make with it

Vision-powered apps like object detection tools or image classification software.

How it helps

MLX-VLM lets you use powerful vision AI models on your Mac without relying on cloud APIs or services.

Real use case example

"A founder wants to develop a product that can detect and classify clothing items in images. They start by installing MLX-VLM and importing the model. Next, they integrate it with their app using Python code to create a working prototype. The outcome is a product that accurately identifies images of clothing items and provides insights for their e-commerce business."

If you're new

When starting out with local AI, pick this up first to grasp the basics of running vision models on your Mac.

If you're senior

When developing complex, self-hosted AI apps, you'll want to reach for MLX-VLM for its performance and flexibility.

Common confusion cleared up

MLX-VLM is specifically designed for running vision language models, not general AI tasks.

Best inside these AI tools
Claude DesktopSelf-hosted
Pairs with
Amazon S3 bucketApple ML Kit
Why we list it on WorkflowStacks: This tool is available to save you costs and give you more control over your AI model deployment.
What it does

MLX-VLM allows startup founders to run and fine-tune powerful vision-language models directly on their Macs, enabling the development of multimodal AI applications

When to use it
  • โ€ขYou're building an AI application that requires both image and text understanding
  • โ€ขYou need to fine-tune a pre-trained vision-language model for your specific use case
  • โ€ขYou prefer to develop and test AI models on your Mac rather than relying on cloud services
Quick start
  1. 1Install MLX-VLM using pip: `pip install mlx-vlm`
  2. 2Clone the MLX-VLM GitHub repository to access example code and models: `git clone https://github.com/Blaizzy/mlx-vlm`
  3. 3Import the library and load a pre-trained model: `from mlx_vlm import VLM; model = VLM.from_pretrained('model_name')`
  4. 4Use the model for inference or fine-tuning: `model.predict(image, text)`
Ready-to-paste prompt
from mlx_vlm import VLM; model = VLM.from_pretrained('vlc-bert-base'); model.predict(image='path/to/image.jpg', text='This is a picture of a cat')
Saves to your device

Topics

apple-silicon
florence2
idefics
llava
llm
local-ai
mlx
molmo
paligemma
pixtral
vision-framework
vision-language-model
vision-transformer
What's inside โ€” free to inspect
No purchase needed

Read the entire source before you build โ€” unlike paid marketplaces that hide it behind a buy button.

10
top-level files
7
folders
79.8M
repo size
MIT
license
Key files
.pre-commit-config.yaml
README.md
requirements.txt
File tree
.github/
agents/
computer_use/
dev/
docs/
examples/
mlx_vlm/
.gitignore
.pre-commit-config.yaml
CONTRIBUTING.md
LICENSE
mkdocs.yml
pyproject.toml
README.md
requirements.txt
update_changelog.py
uv.lock
Quick Actions
Details
Creator
Blaizzy
Language
Python
Category
design
Published
4/16/2024

Are you the creator of this tool? Claim your listing โ†’ and earn 85% of every sale.

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