LFM3-1.7B: pricing, context and benchmarks

What you need to know about LFM3-1.7B

Liquid AI, based in United States, put LFM3-1.7B online on November 6, 2026. It accepts text as input and produces text. Its context window reaches 262,144 tokens, larger than 56 % of the models in the registry, and it can write up to 8,192 tokens in one go.

It is a recent model: real-world feedback and independent scores are still scarce.

LFM3-1.7B pricing

On OpenRouter, LFM3-1.7B costs $0.08 per million input tokens and $0.2 per million output tokens. Counting three tokens read for every token written, its average price is $0.11 per million, more expensive than 11 % of paid models (7.3 times cheaper than the median of $0.8).

A concrete example: a task that sends 2,000 tokens (about 1,500 words) and receives a 500-token answer costs $0.0003. At 1,000 tasks a day, budget $8 a month. The price calculator redoes this with your own volumes.

Tokens already sent and cached are billed at $0.02 per million.

Performance and benchmarks

Epoch AI does not yet publish a capabilities index for LFM3-1.7B. We therefore show no made-up performance rating: only price, context and features count towards its score.

Features, privacy and local use

• It supports tool calling, so it can drive an AI agent, call APIs or MCP servers.
• It can answer in an enforced JSON format (structured outputs).
• It is a reasoning model: it "thinks" before answering, which helps on hard tasks but uses more output tokens.

Its weights are open and downloadable from Hugging Face (other licence): you can run it on your own machines without sending your data to a third party. With 1,728,801,536 billion parameters, it needs about 966,043,139 GB of memory at 4-bit quantisation. Check with the VRAM calculator. It was downloaded 70,034 times on Hugging Face last month.

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