4 models across 2 families · Latest: LFM2.5 8B A1B (2026-05)
Adaptive and efficient AI models
Liquid AI's portfolio covers 4 active models across 2 non-obsolete families, with task labels spanning rag, agents, and long context. Open a model detail page to compare provider routes and sourced benchmarks.
Portfolio context: 5 decision-task tags, 4 active tracked models, latest research stamp 2026-05-28.
Use this portfolio page for
- Teams evaluating rag, agents, and long context across this lab's releases
- Readers comparing families before locking a flagship SKU
- 4 tracked SKUs for migration and pricing follow-ups
Do not stop here for
- Choosing a hosting provider without opening a model page for price ladders
Active models
4
Non-deprecated SKUs linked to this researcher
Active families
2
Non-obsolete families in coverage
Open catalog
1 OSS
0 open-weight (text match)
Decision task tags
5
Mapped to the site-wide task taxonomy
Latest dated release
2026-05-28
LFM2.5 8B A1B
Freshness
2026-05-28
Researched 7d ago
Release cadence
Showing 4 recent dated ships (full timeline below). Latest spotlight: LFM2.5 8B A1B (2026-05-28).
Where this lab wins
- RAG: 1 tracked model with ruler / needle retrieval benchmarks.
- Agentic: 3 tracked models with BFCL, tau-bench, and SWE-bench tool-use coverage.
- Long-context: 1 tracked model with context-token or InfiniteBench-class signal.
- Classification: 2 tracked models with MMLU-class moderation/safety coverage.
Flagship quality / price signal
Anchor SKU: Together LFM2-24B (best sourced coding Q/$ in this portfolio).
Quality / dollar unavailable for this anchor — missing benchmark coverage and/or output token price on the cheapest ladder route (open the model detail after pricing lands).
Liquid AI is an American AI research organization founded in 2023. Adaptive and efficient AI models. Liquid AI ships 2 model families totaling 4 models, with the most recent release LFM2.5 8B A1B in 2026-05. Notable families include LFM-2.5 and LFM-2. Use it as a stable reference for lab background, release coverage, and follow-up model pages as they are added. View official API endpoints, benchmark performance, and coding/agent fit for every Liquid AI model.
About
Liquid AI, an MIT spin-off established in 2023, has rapidly positioned itself at the forefront of generative AI and large language model (LLM) development. Based in Cambridge, Massachusetts, the company's mission is to democratize AI solutions, ensuring they are accessible and controllable by users. Liquid AI's innovative approach transcends traditional transformer-based architectures, marking a significant evolution in the capabilities and efficiency of modern AI systems. Central to Liquid AI's innovation is the creation of Liquid Foundation Models (LFMs), which define a new standard in generative AI technology. These models deliver state-of-the-art performance across various benchmarks, requiring less memory and providing more efficient inference compared to conventional LLMs. Their unique ability to handle diverse data types such as video, audio, text, and time series, empowers broader applications across industries. This versatility is underpinned by their distinctive architecture, which incorporates computational units leveraging principles from dynamical systems, signal processing, and numerical linear algebra, facilitating efficient long-sequence processing. Beyond model development, Liquid AI emphasizes operational and training efficiency. By optimizing their pre- and post-training infrastructure, the company maximizes performance in areas such as multi-step reasoning, long-context recall, and knowledge retention. They distinguish themselves through their "white-box" philosophy, ensuring explainability and transparency in an industry often dominated by opaque "black box" models. Their commitment to open science is evident through active contributions to research and collaborative efforts within the AI community, fostering innovation and accelerating advancements in the field. Liquid AI has already marked significant achievements with the release of language models such as LFM-1B, LFM-3B, and LFM-40B, all of which exhibit exemplary performance within their respective categories. The company has also attracted $46.6 million in seed funding, reflecting robust investor confidence in their pioneering technology and ambitious vision. Collaborations with entities like ITOCHU Techno-Solutions Corporation highlight their expanding global reach and influence. This strategic engagement not only broadens their impact but also underscores the company's role as a trailblazer in advancing AI capabilities.
Featured models
| Model | Released | Context | Input price ($/1M) | Output price ($/1M) | License |
|---|---|---|---|---|---|
| LFM2.5 8B A1B | 2026-05-28 | 128k | - | - | Proprietary |
| LFM2.5 1.2B Instruct | 2026-02-01 | 32k | - | - | Proprietary |
| Together LFM2-24B | 2025-12-01 | 8k | - | - | Open Source |
Model families
Recent releases
- LFM2.5 8B A1B- 2026-05-28
- LFM2.5 1.2B Instruct- 2026-02-01
- Together LFM2-24B- 2025-12-01
- LFM2-24B-A2B- 2025-11-01
FAQ
Who founded Liquid AI and when?
Liquid AI was founded in 2023 and is associated with Cambridge, MA, United States.
What models has Liquid AI released?
Liquid AI ships 4 models across 2 families: LFM-2.5 and LFM-2.
Is Liquid AI's technology open source?
Some Liquid AI models are open-weight (Together LFM2-24B); others are proprietary (LFM2.5 8B A1B, LFM2.5 1.2B Instruct, and LFM2-24B-A2B).
Where is Liquid AI headquartered?
Liquid AI is headquartered in Cambridge, MA, United States.
What is Liquid AI known for?
Adaptive and efficient AI models. Its most prominent tracked family is LFM-2.5.
How can I access Liquid AI's models?
Liquid AI's models are available via OpenRouter.
Explore related pages
Last reviewed: 2026-05-28. Data sourced from public lab announcements and provider documentation.