---
library_name: mlx
license: other
license_name: lfm1.0
license_link: LICENSE
language:
- ar
- zh
- en
- fr
- de
- hi
- id
- it
- ja
- ko
- pl
- pt
- ru
- es
- th
- vi
pipeline_tag: text-generation
tags:
- liquid
- lfm2.5
- edge
- mlx
base_model: LiquidAI/LFM2.5-2.6B
---

<div align="center">
  <img
    src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png"
    alt="Liquid AI"
    style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
  />
  <div style="display: flex; justify-content: center; gap: 0.5em; margin-bottom: 1em;">
    <a href="https://playground.liquid.ai/"><strong>Try LFM</strong></a> &bull;
    <a href="https://docs.liquid.ai/lfm/getting-started/welcome"><strong>Docs</strong></a> &bull;
    <a href="https://leap.liquid.ai/"><strong>LEAP</strong></a> &bull;
    <a href="https://discord.com/invite/liquid-ai"><strong>Discord</strong></a>
  </div>
</div>

# LFM2.5-2.6B-MLX

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

Find more details in the original model card: https://huggingface.co/LiquidAI/LFM2.5-2.6B

## Precisions

| Folder | Precision | Group Size | Size |
|--------|-----------|------------|------|
| [`bf16/`](https://huggingface.co/LiquidAI/LFM2.5-2.6B-MLX/tree/main/bf16) | bf16 | - | 5.02 GB |
| [`8bit/`](https://huggingface.co/LiquidAI/LFM2.5-2.6B-MLX/tree/main/8bit) | 8-bit | 64 | 2.67 GB |
| [`6bit/`](https://huggingface.co/LiquidAI/LFM2.5-2.6B-MLX/tree/main/6bit) | 6-bit | 64 | 2.04 GB |
| [`5bit/`](https://huggingface.co/LiquidAI/LFM2.5-2.6B-MLX/tree/main/5bit) | 5-bit | 64 | 1.76 GB |
| [`4bit/`](https://huggingface.co/LiquidAI/LFM2.5-2.6B-MLX/tree/main/4bit) | 4-bit | 64 | 1.47 GB |
| [`mxfp8/`](https://huggingface.co/LiquidAI/LFM2.5-2.6B-MLX/tree/main/mxfp8) | MXFP8 | 32 | 2.59 GB |
| [`mxfp4/`](https://huggingface.co/LiquidAI/LFM2.5-2.6B-MLX/tree/main/mxfp4) | MXFP4 | 32 | 1.46 GB |
| [`nvfp4/`](https://huggingface.co/LiquidAI/LFM2.5-2.6B-MLX/tree/main/nvfp4) | NVFP4 | 16 | 1.53 GB |

## Use with mlx

`mlx_lm.load` does not resolve subfolders of a HuggingFace repo directly (ml-explore/mlx-lm#403), so download the precision you want first:

```bash
pip install mlx-lm
```

```python
from huggingface_hub import snapshot_download
from mlx_lm import load, generate
from mlx_lm.sample_utils import make_sampler

path = snapshot_download("LiquidAI/LFM2.5-2.6B-MLX", allow_patterns=["4bit/*"])
model, tokenizer = load(f"{path}/4bit")

response = generate(
    model,
    tokenizer,
    prompt="The capital of France is",
    max_tokens=100,
    sampler=make_sampler(temp=0.7),
    verbose=True,
)
```