Organization
Liquid AI
Liquid AI is an AI model developer and developer platform company headquartered in Cambridge, Massachusetts23. This catalog lists 4 open model releases from Liquid AI, under licenses including the LFM Open License v1.0.
Documented roles: Model developer · Developer platform
Liquid AI is a company spun out of MIT CSAIL in 2023 that develops Liquid Foundation Models (LFMs), hybrid models built for efficient deployment on phones, laptops, and other devices. It publishes LFM weights on Hugging Face and offers LEAP, a platform for deploying models on edge devices.1673
Using this organization’s offerings
The detailed audience, self-hosting, pricing, and restrictions review has not yet been completed. Consult the sourced product records below and the publisher’s current terms. Missing detail means unknown, not unavailable.
Key facts
What is and isn’t public
Liquid AI publishes weights for its current LFM models on Hugging Face under the custom LFM Open License v1.0, which conditions commercial use on the licensee's legal entity not exceeding a threshold defined as annual revenue of US$10,000,000 or more. The model cards and release posts reviewed describe training at a high level but do not link training code or training data. LEAP and Apollo are delivery products. This catalog assesses openness per release.1011913147
Products
No hosted model products are recorded for this organization.
Other products
| Product | Kind | Documented delivery and access | Reviewed |
|---|---|---|---|
| LEAP (Liquid Edge AI Platform) (external site: leap.liquid.ai) | Developer tool | Developer platform with an on-device SDK for iOS and Android, a model library, and fine-tuning and bundling tools for running LFMs and other small models locally on devices.73 | Sep 29, 2026 |
| Liquid Apollo (external site: liquid.ai) | Other | Mobile app for iOS and Android that runs Liquid models locally on the device, presented as a way to try private, on-device AI without a cloud connection.83 | Sep 29, 2026 |
Cataloged artifacts
Model families
- LFM (Liquid Foundation Models)Model family
- Liquid AI d1Model family
Model releases
- d1-3BModel releaseAvailability: PublicModel-disclosure tier (USASI rubric v0.2): Open-weight
- LFM2.5-2.6BModel releaseAvailability: PublicModel-disclosure tier (USASI rubric v0.2): Open-weight
- LFM2.5-24B-A2BModel releaseAvailability: PublicModel-disclosure tier (USASI rubric v0.2): Open-weight
- LFM2.5-8B-A1BModel releaseAvailability: PublicModel-disclosure tier (USASI rubric v0.2): Open-weight
Notable documented facts
- Liquid AI releases LFM weights under its own LFM Open License v1.0, which it describes as based on Apache 2.0. The license conditions commercial-use rights on the licensee's legal entity not exceeding a "Threshold" that it defines as annual revenue of US$10,000,000 or more, and states that commercial use by a legal entity that exceeds the Threshold is not licensed. The Threshold does not apply to a qualified non-profit organization's use for non-commercial or research purposes.1011
- In November 2025 Liquid AI published the LFM2 technical report, which describes the hybrid architecture of gated short convolutions with a small number of grouped-query attention blocks and the models' training pipeline.12
In the news
Liquid AI releases LFM2.5-24B-A2B, an open-weight mixture-of-experts model for on-device agents
Liquid AI announced LFM2.5-24B-A2B on October 13, 2026, describing it as a reasoning model built for fast, private agents on-device and as the largest and final model in the LFM2.5 family. The release includes a base model (LFM2.5-24B-A2B-Base) and a post-trained model (LFM2.5-24B-A2B), published as open weights on Hugging Face. The model card lists 24.0B total parameters with 2.45B active per token and a context length of 131,072 tokens, and says the model is not recommended for knowledge-heavy tasks on its own. The weights are released under the LFM Open License v1.0. USASI has not tested this model.
Liquid AI releases open-weight d1 decision models for text, vision, and audio
On October 7, 2026 Liquid AI announced "Open d1", two open-weight decision models that return an answer in a single forward pass instead of generating text. The announcement and model cards describe d1-3B, built on LFM2.5-VL-3B, which takes text and images, and d1-omni-600M, built on LFM2.5-Encoder-350M, which takes text with images or text with up to 30 seconds of speech. The weights are published on Hugging Face, and the announcement says the models have day-one support in llama.cpp. Both model cards give the license as "other" with the name lfm1.0, pointing to a LICENSE file in each repository; the announcement itself does not name a license.
Liquid AI releases LFM2.5-VL-3B-DSpark, a draft model for faster vision-language decoding
Liquid AI announced LFM2.5-VL-3B-DSpark on September 24, 2026. It is an experimental draft model of about 280 million parameters that speeds up text generation by its LFM2.5-VL-3B vision-language model through speculative decoding; Liquid AI says the target model's output is unchanged. The weights are on Hugging Face in Safetensors and GGUF formats, with support in SGLang, MLX-VLM, and llama.cpp. They are released under the LFM Open License v1.0, the same license as other LFM2.5 releases, which limits commercial use by larger companies through an annual-revenue threshold.
Liquid AI releases LFM2.5-VL-3B, an open-weight vision-language model for on-device use
Liquid AI announced LFM2.5-VL-3B on August 12, 2026, a non-reasoning vision-language model that it says answers directly to keep latency low for real-time and on-device applications. The model card says it uses the LFM2.5-2.6B language model as its backbone with a SigLIP2 NaFlex vision encoder, and lists a context length of 32,768 tokens. Weights are on Hugging Face with GGUF, ONNX, and MLX exports, under the LFM Open License v1.0. USASI has not tested this model.
Liquid AI releases LFM2.5-2.6B, an open-weight on-device model trained for agentic workloads
Liquid AI announced LFM2.5-2.6B on August 4, 2026, describing it as a 2.6B-parameter model trained for agentic workloads such as planning, calling tools, and multi-step tasks on devices including phones and CPUs. The base model (LFM2.5-2.6B-Base) and the post-trained model (LFM2.5-2.6B) were published on Hugging Face. The model card lists a context length of 131,072 tokens and says the model is not recommended for agentic coding and knowledge-heavy tasks. The weights are released under the LFM Open License v1.0. USASI has not tested this model.
U.S. eligibility
Eligible · basis: U.S. headquarters
Liquid AI's privacy policy gives the company's contact address as Liquid AI, Inc., 314 Main Street, Cambridge, Massachusetts, and its July 2025 press release carries a Cambridge, Mass. dateline. SEC EDGAR lists the company as incorporated in Delaware and located in Massachusetts. The careers page describes the team as mainly in San Francisco and Boston with a presence in Tokyo; the Tokyo presence does not change the U.S. headquarters.2354
Sources
This listing is not an endorsement or a federal approval.
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APA style
USASI. (2026, October 1). Liquid AI. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/companies/liquid-ai/
BibTeX
@misc{usasi_liquid_ai,
author = {{USASI}},
title = {Liquid AI},
year = {2026},
month = oct,
howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/companies/liquid-ai/}},
note = {United States of America Superintelligence. Last updated 2026-10-01}
}The date is when this page was last updated. Add the date you read it if your style needs one.
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