> ## Documentation Index
> Fetch the complete documentation index at: https://legacy-docs.chunkr.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Model

> Picking a segmentation model

We offer two types of segmentation models for creating bounding boxes - **Fast** and **HighQuality**. This section details the differences between each model, and when a specific model should be used.

## Configuration

You can select which model to use by setting the `model` parameter in the `POST` request body.

```typescript theme={null}
type Model = "Fast" | "HighQuality";
```

## Fast

The Fast model uses [LightGBM](https://lightgbm.readthedocs.io/en/stable/) and runs on CPUs - which makes it much faster than the HighQuality model. It depends on a pre-existing text-layer to create bounding boxes.

This makes it great for text, table and formula segmentation - but it struggles when dealing with images.
It can still segment images that are surrounded/bounded by text to some degree. A good example is graphs that have Y/X axes with labels.

The fast model can't be used for PDFs without a text-layer.

## HighQuality

The HighQuality model uses [VGT](https://arxiv.org/abs/2308.14978) - a state-of-the-art two-stream Vision Grid Transformer.
This model 'has eyes' and can understand layouts with intelligence, so a pre-existing text-layer is not required.
It's better at classifying content into [`segment_type`](/segment#segment-types).

## What will work best for me?

In most cases, we recommend using the Fast model for it's speed and cost benefits,
and using the HighQuality model as a fallback for when the `content` field in the `output` object is empty (i.e when the Fast model returns an empty array).

If you require great table, image or handwriting segmentation consistently, then you should use the HighQuality model.