---
title: LFM2.5-1.2B-Instruct — Fast On-Device LLM | ModelsLab
description: Run LiquidAI's LFM2.5-1.2B-Instruct free LLM locally. 1.2B parameters, 32K context, sub-1GB memory. Generate chat, tool use, and reasoning on-device.
url: https://modelslab.com/liquidai-lfm25-12b-instruct-free
canonical: https://modelslab.com/liquidai-lfm25-12b-instruct-free
type: website
component: Seo/ModelPage
generated_at: 2026-04-15T02:05:30.559642Z
---

Available now on ModelsLab · Language Model

LiquidAI: LFM2.5-1.2B-Instruct (free)
Edge AI. No cloud costs.
---

[Try LiquidAI: LFM2.5-1.2B-Instruct (free)](/models/open_router/liquid-lfm-2.5-1.2b-instruct-free) [API Documentation](https://docs.modelslab.com)

Compact Power. Enterprise Speed.
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Lightning-Fast Inference

### 239 tok/s on CPU

Blazing decode speeds on standard hardware with minimal latency overhead.

Minimal Footprint

### Runs Under 1GB

Deploy on mobile, IoT, and vehicles without memory constraints or infrastructure.

Production-Ready

### Tool Use Built-In

Function calling and multi-step reasoning out of the box for agentic workflows.

Examples

See what LiquidAI: LFM2.5-1.2B-Instruct (free) can create
---

Copy any prompt below and try it yourself in the [playground](/models/open_router/liquid-lfm-2.5-1.2b-instruct-free).

Customer Support Bot

“You are a helpful customer support assistant. A user asks: 'How do I reset my password?' Provide a clear, step-by-step response with tool calls to retrieve account information if needed.”

Math Problem Solver

“Solve this math problem step-by-step: A train travels 120 miles in 2.5 hours. Calculate the average speed and determine how long it takes to travel 300 miles at this rate.”

Code Generation

“Write a Python function that takes a list of numbers and returns the sum of all even numbers. Include error handling for non-numeric inputs.”

Multi-Language Chat

“Respond to this user in their preferred language: 'Bonjour, comment puis-je optimiser mon application pour les appareils mobiles?' Provide technical recommendations.”

For Developers

A few lines of code.
1.2B model. Three lines.
---

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

- **Serverless:** scales to zero, scales to millions
- **Pay per token,** no minimums
- **Python and JavaScript SDKs,** plus REST API

[API Documentation ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())</code>
```

FAQ

Common questions about LiquidAI: LFM2.5-1.2B-Instruct (free)
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[Read the docs ](https://docs.modelslab.com)

### What makes LFM2.5-1.2B-Instruct different from larger models?

### Can I use LFM2.5-1.2B-Instruct for reasoning and tool use?

### What languages does this model support?

### How fast is the inference speed on mobile devices?

### What's the context length and memory requirement?

### Which frameworks support LFM2.5-1.2B-Instruct?

Ready to create?
---

Start generating with LiquidAI: LFM2.5-1.2B-Instruct (free) on ModelsLab.

[Try LiquidAI: LFM2.5-1.2B-Instruct (free)](/models/open_router/liquid-lfm-2.5-1.2b-instruct-free) [API Documentation](https://docs.modelslab.com)

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*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

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*Generated by ModelsLab - 2026-04-15*