LFM2.5-VL-450M is a vision-language model built on the LFM2.5-350M backbone with a SigLIP2 NaFlex vision encoder (86M). It supports OCR, document comprehension, multilingual vision understanding, bounding box prediction, and function calling.

Model Details

Property	Value
Parameters	450M
Precision	4-bit
Group Size	64
Size	0.35 GB
Context Length	32K
Vision Encoder	SigLIP2 NaFlex (86M)
Native Resolution	up to 512x512

Quickstart

uv pip install 'mlx-vlm==0.3.9'

python

from mlx_vlm import load, generate
from mlx_vlm.utils import load_image

model, processor = load("LiquidAI/LFM2.5-VL-450M-MLX-4bit")

image = load_image("photo.jpg")

# Apply chat template (required for LFM2.5-VL)
messages = [{"role": "user", "content": [
    {"type": "image"},
    {"type": "text", "text": "What do you see in this image?"},
]}]
prompt = processor.apply_chat_template(messages, add_generation_prompt=True)

result = generate(
    model,
    processor,
    prompt,
    [image],
    temp=0.1,
    min_p=0.15,
    repetition_penalty=1.05,
    verbose=True,
)
print(result.text)

Recommended Sampling Parameters

Parameter	Value
temperature	0.1
min_p	0.15
repetition_penalty	1.05

License

This model is released under the LFM 1.0 License.