> ## Documentation Index
> Fetch the complete documentation index at: https://deepl-c950b784-docs-language-table-from-v3.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Understanding Model Types

> How the model_type parameter chooses between latency-optimized and quality-optimized translation models, and how DeepL selects the model for each request.

DeepL hosts many AI models for translation and deploys new ones continuously. Rather than asking you to pick a specific model, and update your integration every time models change, the `model_type` parameter of the [`/v2/translate` endpoint](/api-reference/translate/request-translation) lets you state your goal: the lowest possible latency or the highest possible translation quality. DeepL then chooses the most suitable model for your language pair and request.

## Parameter values

The `model_type` parameter accepts three values:

| Value                      | Behavior                                                                             |
| :------------------------- | :----------------------------------------------------------------------------------- |
| `latency_optimized`        | Aims to serve the request as fast as possible (default when `model_type` is omitted) |
| `quality_optimized`        | Aims for the highest translation quality                                             |
| `prefer_quality_optimized` | Legacy value, currently identical to `quality_optimized`                             |

All features and language pairs are compatible with all `model_type` values. As of December 2025, all source and target languages are supported by next-gen models.

When you set `model_type`, the response includes a `model_type_used` field indicating which kind of model served the request:

```sh Example request theme={null}
curl -X POST https://api.deepl.com/v2/translate \
  --header "Content-Type: application/json" \
  --header "Authorization: DeepL-Auth-Key $API_KEY" \
  --data '{
    "text": ["Your order has shipped and will arrive on Tuesday."],
    "target_lang": "DE",
    "model_type": "quality_optimized"
}'
```

```json Example response theme={null}
{
  "translations": [
    {
      "detected_source_language": "EN",
      "text": "Ihre Bestellung wurde versandt und kommt am Dienstag an.",
      "model_type_used": "quality_optimized"
    }
  ]
}
```

## How DeepL selects the model

The parameter expresses a goal, not a model name. DeepL fulfills it on a best-effort basis: for some language pairs and requests, only one model can be used, and not every pair behaves differently between the two values. DeepL may also change which model serves a given `model_type` when the change is a net benefit, for example a quality increase with no significant latency cost, or a large latency reduction with at most a very slight quality trade-off.

This means you never need to update your code for new model releases or track model names: the API keeps choosing the best available model for your stated goal.

## Notes

* `model_type` applies to text translation only. The [`/v2/document` endpoint](/api-reference/document/upload-and-translate-a-document) accepts the parameter without error but ignores it.
* The [`/v3/languages` endpoint](/api-reference/languages/retrieve-supported-languages-by-resource) doesn't yet report `model_type` support per language. This information will be added in a future update.