Translate Text - DeepL Documentation

The text-translation API currently consists of a single endpoint, translate, which is described below. For highest translation quality, we recommend using our next-gen models. For details, please see here. To learn more about context in DeepL API translations, we recommend this article. For more detail about request body parameters, see the Request Body Descriptions section further down on the page. We also provide a spec that is auto-generated from DeepL’s OpenAPI file. You can find it here.

The total request body size for text translation requests must not exceed 128 KiB (128 · 1024 bytes). Please split up your text into multiple calls if it exceeds this limit.

The examples below use our API Pro endpoint https://api.deepl.com. If you’re an API Free user, remember to update your requests to use https://api-free.deepl.com instead.

Example request: text translation (without glossary)

curl -X POST 'https://api.deepl.com/v2/translate' \
--header 'Authorization: DeepL-Auth-Key [yourAuthKey]' \
--header 'Content-Type: application/json' \
--data '{
  "text": [
    "Hello, world!"
  ],
  "target_lang": "DE"
}'

Example request: text translation (with glossary)

curl -X POST 'https://api.deepl.com/v2/translate' \
--header 'Authorization: DeepL-Auth-Key [yourAuthKey]' \
--header 'Content-Type: application/json' \
--data '{
  "text": [
    "Hello, world!"
  ],
  "target_lang": "DE",
  "source_lang": "EN",
  "glossary_id": "[yourGlossaryId]"
}'

Example response

{
  "translations": [
    {
      "detected_source_language": "EN",
      "text": "Hallo, Welt!"
    }
  ]
}

The examples below use our API Pro endpoint https://api.deepl.com. If you’re an API Free user, remember to update your requests to use https://api-free.deepl.com instead.

Example request: text translation (without glossary)

POST /v2/translate HTTP/2
Host: api.deepl.com
Authorization: DeepL-Auth-Key [yourAuthKey] 
User-Agent: YourApp/1.2.3
Content-Length: 45
Content-Type: application/json

{"text":["Hello, world!"],"target_lang":"DE"}

Example request: text translation (with glossary)

POST /v2/translate HTTP/2
Host: api.deepl.com
Authorization: DeepL-Auth-Key [yourAuthKey] 
User-Agent: YourApp/1.2.3
Content-Length: 97
Content-Type: application/json

{"text":["Hello, world!"],"target_lang":"DE","source_lang":"EN","glossary_id":"[yourGlossaryId]"}

Example response

{
  "translations": [
    {
      "detected_source_language": "EN",
      "text": "Hallo, Welt!"
    }
  ]
}

Example request: text translation (without glossary)

import deepl

auth_key = "f63c02c5-f056-..."  # Replace with your key
deepl_client = deepl.DeepLClient(auth_key)

result = deepl_client.translate_text("Hello, world!", target_lang="FR")
print(result.text)  # "Bonjour, le monde !"

Example request: text translation (without glossary)

$authKey = "f63c02c5-f056-..."; // Replace with your key
$deeplClient = new \DeepL\DeepLClient($authKey);

$result = $deeplClient->translateText('Hello, world!', null, 'fr');
echo $result->text; // Bonjour, le monde!

Example request: text translation (without glossary)

var authKey = "f63c02c5-f056-..."; // Replace with your key
var deeplClient = new DeepLClient(authKey);

// Translate text into a target language, in this case, French:
var translatedText = await deeplClient.TranslateTextAsync(
      "Hello, world!",
      LanguageCode.English,
      LanguageCode.French);
Console.WriteLine(translatedText); // "Bonjour, le monde !"
// Note: printing or converting the result to a string uses the output text.

Example request: text translation (without glossary)

import * as deepl from 'deepl-node';

const authKey = "f63c02c5-f056-..."; // Replace with your key
const deeplClient = new deepl.DeepLClient(authKey);

(async () => {
    const result = await deeplClient.translateText('Hello, world!', null, 'fr');
    console.log(result.text); // Bonjour, le monde !
})();

Example request: text translation (without glossary)

import com.deepl.api.*;

class Example {
    DeepLClient deeplClient;

    public Example() throws Exception {
        String authKey = "f63c02c5-f056-...";  // Replace with your key
        deeplClient = new DeepLClient(authKey);
        TextResult result =
                deeplClient.translateText("Hello, world!", null, "fr");
        System.out.println(result.getText()); // "Bonjour, le monde !"
    }
}

These examples are for demonstration purposes only. In production code, the authentication key should not be hard-coded but instead fetched from a configuration file or environment variable. Note that we do not include examples for our client libraries in every single section of this reference, but our client libraries do support all use cases shown on this page.

Please note that the Translate API is intended to be used for translation between different languages, but requests with the same source and target language are still counted toward billing.If trying to convert between variants of the same language (e.g. EN-US to EN-GB), please refer to this guide. Translating between variants of the same language will result in no change to the text.

Request Body Descriptions

text

array[string]

required

Text to be translated. Only UTF-8-encoded plain text is supported. The parameter may be specified multiple times and translations are returned in the same order as they are requested. Each of the parameter values may contain multiple sentences. Up to 50 texts can be sent for translation in one request.

source_lang

string

Language of the text to be translated. If omitted, the API will attempt to detect the language of the text and translate it. You can find supported source languages here.

target_lang

string

required

The language into which the text should be translated. You can find supported target languages here.

enable_beta_languages

boolean

Enables 81 additional beta languages. See the full list.

Note: Set to true (or 1 in url-encoded requests) to enable beta languages. Any request with the enable_beta_languages parameter enabled will use quality_optimized models. Requests combining enable_beta_languages: true and model_type: latency_optimized will be rejected. Beta languages do not support formality or glossaries.

context

string

The context parameter makes it possible to include additional context that can influence a translation but is not translated itself. This additional context can potentially improve translation quality when translating short, low-context source texts such as product names on an e-commerce website, article headlines on a news website, or UI elements.

For example:

When translating a product name, you might pass the product description as context.
When translating a news article headline, you might pass the first few sentences or a summary of the article as context.

For best results, we recommend sending a few complete sentences of context in the same language as the source text. There is no size limit for the context parameter itself, but the request body size limit of 128 KiB still applies to all text translation requests.

If you send a request with multiple text parameters, the context parameter will be applied to each one.

Characters included in the context parameter will not be counted toward billing (i.e., there is no additional cost for using the context parameter, and only characters sent in the text parameter(s) will be counted toward billing for text translation even when the context parameter is included in a request).

model_type

enum

Specifies which DeepL model should be used for translation.Possible values:

latency_optimized: Uses the lowest latency translation models available (usually classic models; default parameter value)
quality_optimized: Uses the highest quality translation models available (currently next-gen models)
prefer_quality_optimized: Same as quality_optimized, with fallback to classic models if no next-gen model is present (as of December 2025, all languages have next-gen models)

When the model_type parameter is set, the response includes a model_type_used field indicating which model was used.

Tag handling v2 is compatible only with next-gen models and implicitly sets model_type to quality_optimized. Setting both model_type=latency_optimized and tag_handling_version=v2 will return an error.

See About the model_type parameter for more details.

split_sentences

string

Sets whether the translation engine should first split the input into sentences. For text translations where tag_handling is not set to html, the default value is 1, meaning the engine splits on punctuation and on newlines.

For text translations where tag_handling=html, the default value is nonewlines, meaning the engine splits on punctuation only, ignoring newlines.

The use of nonewlines as the default value for text translations where tag_handling=html is new behavior that was implemented in November 2022, when HTML handling was moved out of beta.

Possible values are:

0 - no splitting at all; whole input is treated as one sentence
1 (default when tag_handling is not set to html) - splits on punctuation and on newlines
nonewlines (default when tag_handling=html) - splits on punctuation only, ignoring newlines

For applications that send one sentence per text parameter, we recommend setting split_sentences to 0, in order to prevent the engine from splitting the sentence unintentionally.

Please note that newlines will split sentences when split_sentences=1. We recommend cleaning files so they don’t contain breaking sentences or setting the parameter split_sentences to nonewlines.

Please note that this value will be ignored when using next-gen models (model_type_used=quality_optimized) and a value of:

0 will be used if tag_handling is not enabled
nonewlines will be used if tag_handling is enabled

…as these settings yield the best quality.

preserve_formatting

boolean

Sets whether the translation engine should respect the original formatting, even if it would usually correct some aspects.

The formatting aspects affected by this setting include:

Punctuation at the beginning and end of the sentence
Upper/lower case at the beginning of the sentence

Note: for requests sent as URL-encoded forms, boolean values should be specified as “1” or “0”.

formality

string

Sets whether the translated text should lean towards formal or informal language. This feature currently only works for target languages DE (German), FR (French), IT (Italian), ES (Spanish), ES-419 (Latin American Spanish), NL (Dutch), PL (Polish), PT-BR and PT-PT (Portuguese), JA (Japanese), and RU (Russian). Learn more about the plain/polite feature for Japanese ↗️.

Setting this parameter with a target language that does not support formality will fail, unless one of the prefer_… options are used. Possible options are:

default (default)
more - for a more formal language
less - for a more informal language
prefer_more - for a more formal language if available, otherwise fallback to default formality
prefer_less - for a more informal language if available, otherwise fallback to default formality

glossary_id

string

Specify the glossary to use for the translation.

Important: This requires the source_lang parameter to be set and the language pair of the glossary has to match the language pair of the request.

style_id

string

Specify the style rule list to use for the translation which can be used to customize translations according to the selected formatting and style conventions.

The target language has to match the language of the style rule list.Additionally, any request with the style_id parameter enabled will default to use the quality_optimized model type. Requests combining style_id and model_type: latency_optimized will be rejected.

custom_instructions

array[string]

Specify a list of instructions to customize the translation behavior. Up to 10 custom instructions can be specified, each with a maximum of 300 characters.

The target language must be de, en, es, fr, it, ja, ko, zh or any variants of these languages.Any request with the custom_instructions parameter enabled will default to use the quality_optimized model type. Requests combining custom_instructions and model_type: latency_optimized will be rejected.

show_billed_characters

boolean

When true, the response will include an additional key-value pair with the key billed_characters and a value that is an integer showing the number of characters from the request that will be counted by DeepL for billing purposes.

For example: “billed_characters”: 42

At some point in the future, we intend to include billed_characters in the API response by default, at which point it will be necessary to set show_billed_characters to false in order for an API response not to include billed_characters. We will notify users in advance of making this change.For requests sent as URL-encoded forms, boolean values should be specified as “1” or “0”.

tag_handling

string

Sets which kind of tags should be handled. Options currently available:

xml: Enable XML tag handling; see XML handling.
html: Enable HTML tag handling; see HTML handling.

tag_handling_version

string

Select which version of the tag handling algorithm should be used. See tag handling v2.

v2: Use the improved v2 algorithm.
v1: Use the previous v1 algorithm.

outline_detection

boolean

The automatic detection of the XML structure won’t yield best results in all XML files. You can disable this automatic mechanism altogether by setting the outline_detection parameter to false and selecting the tags that should be considered structure tags. This will split sentences using the splitting_tags parameter.

In the example below, we achieve the same results as the automatic engine by disabling automatic detection with outline_detection=false and setting the parameters manually to tag_handling=xml, split_sentences=nonewlines, and splitting_tags=par,title.

Example request

  <document>
    <meta>
      <title>A document's title</title>
    </meta>
    <content>
      <par>This is the first sentence. Followed by a second one.</par>
      <par>This is the third sentence.</par>
    </content>
  </document>

Example response

  <document>
    <meta>
      <title>Der Titel eines Dokuments</title>
    </meta>
    <content>
      <par>Das ist der erste Satz. Gefolgt von einem zweiten.</par>
      <par>Dies ist der dritte Satz.</par>
    </content>
  </document>

While this approach is slightly more complicated, it allows for greater control over the structure of the translation output.

Note: For requests sent as URL-encoded forms, boolean values should be specified as “1” or “0”.

non_splitting_tags

array[string]

Comma-separated list of XML tags which never split sentences. Learn more

splitting_tags

array[string]

Comma-separated list of XML tags which always cause splits. Learn more

ignore_tags

array[string]

Comma-separated list of XML tags that indicate text not to be translated. Learn more

About the model_type parameter

The model_type parameter lets a user specify if they would like to optimize for speed until a request is served (latency) or translation quality. This is done on a best-effort basis by DeepL, not every language pair and feature must behave differently depending on this parameter. Currently, the DeepL translation API defaults to the classic models if no model_type is included in the requests, except for certain languages (e.g. Thai, which is next-gen only) or certain features (e.g. tag handling v2, which only allows quality_optimized). Note that the API intentionally does not allow the user to specify a model, but rather their goal, so that the DeepL backend can choose the most suitable model for the user (this avoids users constantly having to update their code with new model versions and learning many different models name and their specifics). As of December 2025, all source and target languages are supported by next-gen models. Please note that DeepL reserves the right to quietly change which model serves e.g. a model_type=quality_optimized request, as long as we think it is a net benefit to the user (e.g. no significant latency increase, but a quality increase, or a significant latency reduction with no or only very slight decrease in quality). The /languages endpoint has not yet been updated to include information about model_type support, but we expect to make such a change in the future.

Multiple Sentences

The translation function will (by default) try to split the text into sentences before translating. Splitting normally works on punctuation marks (e.g. ”.” or ”;”), though you should not assume that every period will be handled as a sentence separator. This means that you can send multiple sentences as a value of the text parameter. The translation function will separate the sentences and return the whole translated paragraph. In some cases, the sentence splitting functionality may cause issues by splitting sentences where there is actually only one sentence. This is especially the case if you’re using special/uncommon character sequences which contain punctuation. In this case, you can disable sentence splitting altogether by setting the parameter split_sentences to 0. Please note that this will cause overlong sentences to be cut off, as the DeepL API cannot translate overly long sentences. In this case, you should split the sentences manually before submitting them for translation.

cURL
HTTP Request

The example below uses our API Pro endpoint https://api.deepl.com. If you’re an API Free user, remember to update your requests to use https://api-free.deepl.com instead.

Example request: multiple sentences

curl -X POST 'https://api.deepl.com/v2/translate' \
--header 'Authorization: DeepL-Auth-Key [yourAuthKey]' \
--header 'Content-Type: application/json' \
--data '{
  "text": [
    "The table is green. The chair is black."
  ],
  "target_lang": "DE"
}'

Example response

{
  "translations": [
    {
      "detected_source_language": "EN",
      "text": "Der Tisch ist grün. Der Stuhl ist schwarz."
    }
  ]
}

The example below uses our API Pro endpoint https://api.deepl.com. If you’re an API Free user, remember to update your requests to use https://api-free.deepl.com instead.

Example request: multiple sentences

POST /v2/translate HTTP/2
Host: api.deepl.com
Authorization: DeepL-Auth-Key [yourAuthKey] 
User-Agent: YourApp/1.2.3
Content-Length: 71
Content-Type: application/json

{"text": ["The table is green. The chair is black."],"target_lang":"DE"}

Example response

{
  "translations": [
    {
      "detected_source_language": "EN",
      "text": "Der Tisch ist grün. Der Stuhl ist schwarz."
    }
  ]
}

Translating Large Volumes of Text

There are a few methods to translate larger volumes of text:

If your text is contiguous, you can submit whole paragraphs to be translated in one request and with one text parameter. Prior to translation, your text will be split into sentences and translated accordingly.
The translate function can take several text parameters and will return translations of each such parameter separately in the same order as they are requested (see example below). Each of the parameter values may contain multiple sentences. Up to 50 texts can be sent for translation per request.
You can make parallel requests by calling the translate function from several threads/processes.

cURL
HTTP Request

The example below uses our API Pro endpoint https://api.deepl.com. If you’re an API Free user, remember to update your requests to use https://api-free.deepl.com instead.

Example request: large volumes of text

curl -X POST 'https://api.deepl.com/v2/translate' \
--header 'Authorization: DeepL-Auth-Key [yourAuthKey]' \
--header 'Content-Type: application/json' \
--data '{
  "text": [
    "This is the first sentence.",
    "This is the second sentence.",
    "This is the third sentence."
  ],
  "target_lang": "DE"
}'

Example response

{
  "translations": [
    {
      "detected_source_language": "EN",
      "text": "Das ist der erste Satz."
    },
    {
      "detected_source_language": "EN",
      "text": "Das ist der zweite Satz."
    },
    {
      "detected_source_language": "EN",
      "text": "Dies ist der dritte Satz."
    }
  ]
}

The example below uses our API Pro endpoint https://api.deepl.com. If you’re an API Free user, remember to update your requests to use https://api-free.deepl.com instead.

Example request: large volumes of text

POST /v2/translate HTTP/2
Host: api.deepl.com
Authorization: DeepL-Auth-Key [yourAuthKey] 
User-Agent: YourApp/1.2.3
Content-Length: 120
Content-Type: application/json

{"text":["This is the first sentence.","This is the second sentence.","This is the third sentence."],"target_lang":"DE"}

Example response

{
  "translations": [
    {
      "detected_source_language": "EN",
      "text": "Das ist der erste Satz."
    },
    {
      "detected_source_language": "EN",
      "text": "Das ist der zweite Satz."
    },
    {
      "detected_source_language": "EN",
      "text": "Dies ist der dritte Satz."
    }
  ]
}

In-Text Markup

You should take precaution with uncommon characters you may have embedded in your texts. Uncommon character sequences, which may be recognized markers within your system, might get translated or removed, resulting in a corrupted structure. In this case, it is advisable to either split the text so that there is no need to send markers, or to convert your markers to XML tags and enable XML handling or HTML handling.

API Reference

​Request Body Descriptions

​About the model_type parameter

​Multiple Sentences

​Translating Large Volumes of Text

​In-Text Markup

Request Body Descriptions

About the model_type parameter

Multiple Sentences

Translating Large Volumes of Text

In-Text Markup