Liquid AI: LFM2-8B-A1B

This model is no longer available.

Add AI to your application with Puter.js.

Explore Other Models

Model Card

LFM2-8B-A1B is a sparse Mixture-of-Experts language model from Liquid AI with 8.3B total parameters but only 1.5B active per token, using 32 experts per MoE block with top-4 active per token.

This design delivers 3-4B dense model quality at the compute cost of a 1.5B model, making it faster than Qwen3-1.7B in practice. Verified benchmarks include GSM8K 84.4%, MATH500 74.2%, IFEval 77.6%, and MMLU-Pro 37.4%.

For API developers, it is a strong choice for latency-sensitive applications requiring larger-model quality at minimal compute cost — ideal for high-throughput pipelines where speed and efficiency are priorities.

Context Window 33K

tokens

Max Output N/A

tokens

Input Cost $0.01

per million tokens

Output Cost $0.02

per million tokens

Release Date Jun 1, 2025

Code Example

Add AI to your app with the Puter.js AI API, no API keys or setup required.

// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms").then(response => {
    document.body.innerHTML = response.message.content;
});

<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("Explain quantum computing in simple terms").then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

More AI Models From Liquid AI

Find other Liquid AI models →

Chat

LFM2.5-24B-A2B

LFM2.5-24B-A2B is a sparse Mixture-of-Experts reasoning model from Liquid AI with 24B total parameters and about 2.45B active per token. It has a 131K context window and always produces a reasoning trace before answering. It is built for agents and tool calling. Liquid AI reports IFEval 96.75, IFBench 74.69, BFCLv4 65.01, ToolSandbox 80.71 and SWE-Bench Verified 51.00. It scores higher than Qwen3.6-35B-A3B and Gemma-4-26B-A4B-it on most agentic and instruction-following tests, but trails Qwen3.6-35B-A3B on coding (SWE-Bench Verified 66.20) and GPQA Diamond (83.69 vs. 74.42). It suits developers building tool-calling agents, especially with retrieval or web search. Liquid AI advises against using it alone for knowledge-heavy tasks or where direct, non-reasoning replies are needed.

Frequently Asked Questions

How do I use LFM2-8B-A1B?

LFM2-8B-A1B is no longer available through Puter.js. Explore other AI models for alternatives.

What is the pricing for LFM2-8B-A1B?

LFM2-8B-A1B costs $0.01 per 1M input tokens and $0.02 per 1M output tokens.

	Price per 1M tokens
Input	$0.01
Output	$0.02

Who created LFM2-8B-A1B?

LFM2-8B-A1B was created by Liquid AI and released on Jun 1, 2025.

What is the context window of LFM2-8B-A1B?

LFM2-8B-A1B supports a context window of 33K tokens. For reference, that is roughly equivalent to 66 pages of text.

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the LFM2-8B-A1B API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.

Get started with Puter.js

Add AI to your application without worrying about API keys or setup.

Explore Models View Tutorials