Liquid AI

Liquid AI is an American general-purpose AI company founded in Boston in 2023 and spun out of MIT, focused on building next-generation foundation models based on liquid neural networks. Founded by MIT professor Ramin Hasani, Mathias Lechner, and Daniela Rus, it drew attention to LFM-40B's inference efficiency and raised $250 million in 2024. On AI, Liquid AI has released its LFM (Liquid Foundation Models) family, including LFM-1B, LFM-3B, LFM-40B, and the newer LFM2 series.

AI Models

d1.1

Liquid AI

d1.1 is Liquid AI's structured decision model, served as a System One endpoint and the successor to d1. Send a state along with typed questions, and it returns a choice, a score, or a yes/no answer, each with a probability taken directly from the model rather than written out as text. It uses the same /v1/systemone schema as other OpenRouter Decisions models, so it suits routing, classification, and policy checks that need a fast, scored answer instead of prose.

Context: 65.5K
Max output: -
Released: 2026-10-27

Input: $0.02 /M

d1-ultra

Liquid AI

d1-ultra is Liquid AI's largest decision model, served as a System One endpoint. Send a state of text and images along with typed questions, and it returns a choice, a score, or a yes/no answer, each with a probability taken directly from the model rather than written out as text. It uses the same /v1/systemone schema as other OpenRouter Decisions models, so it suits routing, classification, moderation, and visual checks that need a fast, scored answer instead of prose.

Context: 32.8K
Max output: -
Released: 2026-10-15

Input: $0.042 /M

LFM2.5-24B-A2B

Liquid AI

LFM2.5-24B-A2B is a mixture-of-experts reasoning model from Liquid AI with 24B total and 2.45B active parameters. It always reasons before answering and is built for agents that call tools. Liquid recommends pairing it with retrieval or web search for knowledge-heavy tasks.

Context: 128K
Max output: -
Released: 2026-10-13

Input: $0.05 /M
Output: $0.7 /M

d1

Liquid AI

d1 is Liquid AI's structured decision model, served as a System One endpoint. Send a state along with typed questions, and it returns a choice, a score, or a yes/no answer, each with a probability taken directly from the model rather than written out as text. It uses the same /v1/systemone schema as other OpenRouter Decisions models, so it suits routing, classification, and policy checks that need a fast, scored answer instead of prose.

Context: 65.5K
Max output: -
Released: 2026-10-01

Input: $0.02 /M

LFM2.5-2.6B

Liquid AI

LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or knowledge-heavy tasks. Prompts and outputs may be retained and used to train Liquid models.

AI Models

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