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---
base_model:
- LiquidAI/LFM2-1.2B
---
# LFM2-1.2B
Run **LFM2-1.2B** on Android devices powered by Qualcomm NPU.
## Quickstart
See [Documentation](https://docs.nexa.ai/nexa-sdk-android/quickstart)
## Model Description
**LFM2-1.2B** is part of Liquid AI’s second-generation **LFM2** family, designed specifically for **on-device and edge AI deployment**.
With **1.2 billion parameters**, it strikes a balance between compact size, strong reasoning, and efficient compute utilization—ideal for running on CPUs, GPUs, or NPUs.
LFM2 introduces a **hybrid Liquid architecture** with **multiplicative gates and short convolutions**, enabling faster convergence and improved contextual reasoning.
It demonstrates up to **3× faster training** and **2× faster inference** on CPU compared to Qwen3, while maintaining superior accuracy across multilingual and instruction-following benchmarks.
## Features
-**Speed & Efficiency** – 2× faster inference and prefill].
- 🧠 **Hybrid Liquid Architecture** – Combines multiplicative gating with convolutional layers for better reasoning and token reuse.
- 🌍 **Multilingual Competence** – Supports diverse languages for global use cases.
- 🛠 **Flexible Deployment** – Runs efficiently on CPU, GPU, and NPU hardware.
- 📈 **Benchmark Performance** – Outperforms similarly-sized models in math, knowledge, and reasoning tasks.
## Use Cases
- Edge AI assistants and voice agents
- Offline reasoning and summarization on mobile or automotive devices
- Local code and text generation tools
- Lightweight multimodal or RAG pipelines
- Domain-specific fine-tuning for vertical applications (e.g., finance, robotics)
## Inputs and Outputs
**Input**
- Text prompts or structured instructions (tokenized sequences for API use).
**Output**
- Natural-language or structured text generations.
- Optionally: logits or embeddings for advanced downstream integration.
## License
This model is released under the **Creative Commons Attribution–NonCommercial 4.0 (CC BY-NC 4.0)** license.
Non-commercial use, modification, and redistribution are permitted with attribution.
For commercial licensing, please contact **[email protected]**.