Liquid AI: LFM2-8B-A1B

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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>

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LFM2-24B-A2B

LFM2 24B A2B is a sparse Mixture-of-Experts model from Liquid AI featuring a novel hybrid architecture that combines gated short convolution blocks with Grouped Query Attention in a 3:1 ratio, developed through hardware-in-the-loop architecture search. With 24 billion total parameters but only ~2 billion active per token, it delivers high throughput while outperforming larger MoE competitors like Qwen3-30B-A3B in throughput benchmarks. It supports 9 languages, a 32K context window, native function calling, and structured outputs. A strong API choice for high-volume multi-agent pipelines, RAG backends, and multilingual applications that demand low per-token cost alongside capable general reasoning.

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LFM2.5-1.2B-Instruct

LFM 2.5 1.2B Instruct is a compact instruction-tuned language model from Liquid AI, designed to deliver best-in-class performance at the 1-billion-parameter scale. Trained on 28 trillion tokens with reinforcement learning, it achieves strong scores across knowledge (MMLU-Pro: 44.35), reasoning (GPQA: 38.89), and instruction following (IFEval: 86.23) — outperforming similarly sized models like Llama-3.2-1B and Gemma-3-1B on these benchmarks. The model supports tool use, structured outputs, and function calling, making it a solid choice for lightweight agentic pipelines, chatbots, and latency-sensitive API integrations where cost and throughput matter most.

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LFM2.5-1.2B-Thinking

LFM 2.5 1.2B Thinking is a compact reasoning model from Liquid AI that generates explicit chain-of-thought traces before producing answers, enabling more reliable performance on multi-step problems at the 1-billion-parameter scale. Compared to its instruct sibling, it shows major benchmark gains in math reasoning (MATH-500: 88 vs. 63), instruction following (Multi-IF: 69 vs. 61), and tool use (BFCLv3: 57 vs. 49). It matches or exceeds Qwen3-1.7B on most reasoning benchmarks despite having 40% fewer parameters. Well-suited for API use cases involving agentic tool calling, math, and code — anywhere a reasoning trace meaningfully improves answer quality.

Frequently Asked Questions

How do I use LFM2-8B-A1B?

You can access LFM2-8B-A1B by Liquid AI through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.

Is LFM2-8B-A1B free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add LFM2-8B-A1B to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.

What is the pricing for LFM2-8B-A1B?
Pricing for LFM2-8B-A1B is based on the number of input and output tokens used per request.
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.

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