Hugging Face announced that Jun Kim has joined the company to lead and support the oMLX project full time. The company says it is fully committed to local (on-device) AI, and regards MLX — Apple’s framework for local AI optimized for Apple Silicon — as a central part of that ecosystem.
What MLX is and why it matters
MLX is Apple’s framework for running AI locally, with optimizations for Apple Silicon hardware. Hugging Face noted that MLX became widely noticed after it was given as a Christmas gift by Awni and Angelos in 2023, and that the Hugging Face Hub is a place where people find and contribute MLX models.
Usage of open, local AI is accelerating, and Hugging Face says it supports a healthy ecosystem where developers can find the tools that work for them.
Impact on oMLX
According to the announcement, hiring Jun should bring stability and potentially faster development to oMLX: the project is moving from a side project to a fully maintained and funded effort. That change is intended to let Jun better coordinate contributors and build for the long term.
oMLX will remain under the Apache 2.0 license, and Jun Kim will continue to lead the project as before.
Broader impact for the MLX ecosystem
Hugging Face’s stated goal is to unblock the community’s ability to run local AI in various forms by providing tools and building blocks to make that possible. They expect oMLX to act as a testbed for new ideas while leveraging foundational work from existing dependencies such as mlx-lm and mlx-vlm.
The company also expressed a desire to upstream useful work to the projects and libraries where it makes sense, arguing that strong modeling and inference libraries benefit the wider community.
Collaboration and concrete focus areas
Hugging Face said it has been collaborating with projects including mlx-lm, mlx-vlm, and LMStudio. The announcement mentions contributors Cheng, Prince, and Yagil and their teams, and expresses hope to strengthen those relationships to better serve the community together.
A concrete technical focus is speeding the transition from a transformers model definition to a reference MLX implementation that can be consumed by different engines. Since the transformers library is the reference for many model definitions, Hugging Face wants to streamline the process so new transformers models run on MLX more easily.
Outlook
Hugging Face said it is excited about the future and welcomed Jun Kim to the team. The move is presented as support for the growth of open, local AI while keeping oMLX’s open-source license and leadership unchanged.
