Liquid AI · language model
LFM2.5-24B-A2B: pricing, context and benchmarks
LFM2.5-24B-A2B is Liquid AI's model released on October 13, 2026. It costs $0.05 per million input tokens and $0.7 per million output tokens, with a 128K-token context window. No independent score has been published for it so far.
| Price | 23/30 | |
|---|---|---|
| Context | 3/15 | |
| Features | 15/15 |
What you need to know about LFM2.5-24B-A2B
Liquid AI, based in United States, put LFM2.5-24B-A2B online on October 13, 2026. It accepts text as input and produces text. Its context window reaches 128,000 tokens, larger than 19 % 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.
LFM2.5-24B-A2B pricing
On OpenRouter, LFM2.5-24B-A2B costs $0.05 per million input tokens and $0.7 per million output tokens. Counting three tokens read for every token written, its average price is $0.213 per million, more expensive than 22 % of paid models (3.6 times cheaper than the median of $0.76).
A concrete example: a task that sends 2,000 tokens (about 1,500 words) and receives a 500-token answer costs $0.0005. At 1,000 tasks a day, budget $14 a month. The price calculator redoes this with your own volumes.
Tokens already sent and cached are billed at $0.025 per million.
Performance and benchmarks
Epoch AI does not yet publish a capabilities index for LFM2.5-24B-A2B. 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 23,971,585,280 billion parameters, it needs about 13,395,167,112 GB of memory at 4-bit quantisation. Check with the VRAM calculator. It was downloaded 19,800 times on Hugging Face last month.
Other Liquid AI models
| Model | Released | Avg. price | ECI |
|---|---|---|---|
| LFM2.5-2.6B | Aug 11, 2026 | Free | — |
Verdict
Computed score: 68/100, from public data (performance, price, context, features).
Strengths
- Low price: cheaper than 78 % of paid models.
- Open weights: self-hostable, your data stays with you.
- Agent-ready: tool calling and structured JSON output.
Limitations
- No independent score published: performance cannot be verified.
- Text only: reads neither images nor files.
Avoid if…
- you want to host it on a single consumer computer (≈ 13,395,167,112 GB needed at 4-bit).
Alternatives
- GPT-4o-mini$0.26
- GPT-4o-mini (2024-07-18)$0.26
- Command R (08-2024)$0.26
- Nemotron 3.5 Content Safety$0.2
- Qwen3 30B A3B$0.22
- Hunyuan A13B Instruct$0.25
Comparisons and tools
Learn more
Frequently asked questions
How much does LFM2.5-24B-A2B cost?
$0.05 per million input tokens and $0.7 per million output tokens on OpenRouter (checked October 25, 2026). A task with 2,000 tokens read and 500 written costs $0.0005.
How big is LFM2.5-24B-A2B's context window?
128,000 tokens, roughly 96,000 words, with a maximum of 8,192 output tokens.
Can LFM2.5-24B-A2B run locally?
Yes, its weights are published under the other licence. Expect about 13,395,167,112 GB of memory at 4-bit.
Is LFM2.5-24B-A2B suitable for an AI agent?
Technically yes: it supports tool calling and structured outputs. Then check its cost for your volume.
What are the alternatives to LFM2.5-24B-A2B?
The closest models on price and performance are GPT-4o-mini, GPT-4o-mini (2024-07-18), and Command R (08-2024).
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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score