Credit: Liquid AI Liquid AI has tuned Liquid Context to run on Qualcomm’s Snapdragon chips. The software builds a picture of the user on the device itself. The company announced the work at Qualcomm’s Snapdragon Summit in Maui on Wednesday. A day later, it released a tool that speeds up its vision model on devices.
Liquid AI, spun out of MIT in 2023, builds AI models meant to run on phones, laptops, cars and robots rather than in data centres. What Liquid Context does With the user’s permission, Liquid Context learns routines, preferences and needs from signals on the device. It keeps that picture up to date. It then passes the relevant parts to the AI agents the user chooses.
Those can be Liquid AI’s own Liquid Agent or other companies’ agents. They can run on the device, in the cloud or both. The company said the personal context stays on the device. Agents only get what the user allows.
The layer runs in the background on the Hexagon NPU, Qualcomm’s chip block for AI. That way, a cloud model does not have to process every update. “Personal AI starts with understanding how you live and what you need, when you need it,” said Ramin Hasani, Liquid AI’s chief executive and co-founder. Liquid AI gave three examples, which it called illustrative. In one, a message says the user’s child is sick and needs collecting from school early.
An agent checks the calendar, works out which meetings can move and drafts emails for the user to approve. In another, a smartwatch records a personal best on a run. When the user gets back to the car, the car’s agent congratulates them and cools the cabin to their liking. Qualcomm already supplies chips to carmakers, and BMW handed it its cars’ computing in July.
What Qualcomm gets Device makers can build Liquid Context in as a standard feature, and can also license Liquid Agent. That agent runs on LFM2.5-2.6B, a model with 2.6 billion parameters. Liquid AI has tuned it for the Hexagon NPU. The two companies said they are “exploring additional opportunities” to work together.
Neither company named a device maker. “By combining our industry-leading Snapdragon platforms with innovative AI technologies from companies like Liquid AI, we’re helping accelerate the next generation of Agentic AI experiences,” said Durga Malladi, an executive vice president at Qualcomm Technologies. Qualcomm is also making chips for data centres, including custom silicon for Amazon’s AWS. OpenAI, meanwhile, is working on its own devices. A faster vision model On Thursday, Liquid AI released a draft model for LFM2.5-VL-3B.
That model reads images as well as text. It uses a method called speculative decoding. A small draft model guesses the next few words, and the main model checks them in one pass, so the answer comes out faster with the same quality. The drafter has about 280 million parameters and adds 8.9% to the model’s size.
Liquid AI said it speeds up decoding by up to 3.13 times on an M5 Max MacBook Pro and up to 2.66 times on an Nvidia H100 GPU. Whole answers arrive up to 2.62 and 2.27 times faster. The company trained it only on AMD hardware. The gains are smaller than they look for many tasks, Liquid AI said.
The method does not speed up reading the image or the prompt. On edge devices, those steps take a bigger share of the total time, which caps the overall speed-up. The model is free to download on Hugging Face.
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