---
library_name: mlx
license: other
license_name: lfm1.0
license_link: https://huggingface.co/LiquidAI/LFM2.5-8B-A1B/blob/main/LICENSE
tags:
- mlx
- oq
- quantized
- lfm2.5
- edge
pipeline_tag: text-generation
base_model: LiquidAI/LFM2.5-8B-A1B
---

# LFM2.5-8B-A1B-oQ5

This model is an **MLX oQ5 quantized** version of [LiquidAI/LFM2.5-8B-A1B](https://huggingface.co/LiquidAI/LFM2.5-8B-A1B), quantized using [oQ](https://github.com/jundot/omlx) (oMLX v0.3.12) mixed-precision quantization.

## Quantization details

- **Model type**: lfm2_moe
- **Bits**: 5
- **Group size**: 64
- **Format**: MLX safetensors

## Base Model: LFM2.5-8B-A1B

LFM2.5 is a new family of hybrid models designed for on-device deployment by Liquid AI. It builds on the LFM2 architecture with extended pre-training and reinforcement learning.

### Model Details

| Property | Value |
| --- | --- |
| Total parameters | 8.3B |
| Active parameters | 1.5B |
| Number of layers | 24 (18 double-gated LIV conv + 6 GQA) |
| Training budget | 38 trillion tokens |
| Context length | 131,072 |
| Vocabulary size | 128,000 |
| Languages | English, Arabic, Chinese, French, German, Japanese, Korean, Portuguese, Spanish |

### Recommended Generation Parameters

- `temperature: 0.2`
- `top_p: 80`
- `repetition_penalty: 1.05`

### Chat Template

LFM2.5 uses a ChatML-like format:

```
<|startoftext|><|im_start|>system
You are a helpful assistant trained by Liquid AI.<|im_end|>
<|im_start|>user
What is C. elegans?<|im_end|>
<|im_start|>assistant
```

### Citation

```bibtex
@article{liquidAI20268BA1B,
  author  = {Liquid AI},
  title   = {LFM2.5-8B-A1B: Personal Assistant On Your Laptop},
  journal = {Liquid AI Blog},
  year    = {2026},
  note    = {www.liquid.ai/blog/lfm2-5-8b-a1b},
}
```

```bibtex
@article{liquidai2025lfm2,
  title   = {LFM2 Technical Report},
  author  = {Liquid AI},
  journal = {arXiv preprint arXiv:2511.23404},
  year    = {2025}
}
```