128 GB of memory is nice, but you can get started with local agentic AI workflows with much less. By connecting gemma 4 in @lmstudio to MATLAB MCP Server, you can run a local AI model that uses MATLAB as a tool on a 16 GB RAM MacBook Pro. 🔗 spr.ly/6010BD2aXC

For WWDC, we worked with Apple to run Kimi K2.6, a 1T-parameter model, across a cluster of four Mac Studios using a preview version of LM Studio. We showcased secure remote access from a MacBook Neo and iPhone using LM Link. A glimpse of your own private, frontier-scale AI.

One of the coolest in person demos at #wwdc26 was @lmstudio running massive local models on 4 daisy chained Mac Studios with a total of 2tb memory Then they pulled out an iPhone and chatted with those models remotely over a secure connection I need to find a use for this

LM Studio on stage for WWDC at the Steve Jobs Theater demonstrating MLX distributed on 4 Mac Studio! Coming later this year @lmstudio 👾

We made @lmstudio's MLX Engine a lot faster in the latest release. Read the technical deep dive from @ostensiblyneil. P.S. it's all open source!