Models and media

Completion models

const responses = new GrokClient({ apiKey })
  .completionModel('grok-4.5')

const chat = new GrokClient({
  apiKey,
  completionApi: 'chat',
}).completionModel('grok-4.5')

Choose Responses for provider tools and native source normalization. Choose Chat only for workflows that require that endpoint and do not use provider-executed tools.

Image generation

const result = await grok.imageGenerationModel().imageGeneration({
  prompt: 'A robot reviewing a pull request in a glass office',
  width: 1024,
  height: 1024,
})

The default model is grok-imagine-image. The adapter supports the documented ratio set, maps 13:6 to 19.5:9, maps 6:13 to 9:19.5, and sends auto for other ratios. Invalid, non-finite, or non-positive dimensions throw.

Provider base64 images are decoded directly. URL images are fetched and returned as bytes; a URL response without fetch is an error.

Text-to-speech

const speech = await grok.audioGenerationModel().audioGeneration({
  text: 'The run is complete.',
  voice: 'eve',
  speed: 1,
  additionalParams: {
    language: 'en',
    output_format: { codec: 'mp3', sample_rate: 24_000 },
  },
})

Speed must be exactly 1. Additional parameters must be an object.

Transcription

const result = await grok.transcriptionModel().transcription({
  data: speech.audio,
  filename: 'speech.mp3',
  language: 'en',
})

The adapter uploads multipart bytes to the STT endpoint and retains provider JSON as rawResponse. A response without recognized text is rejected. Anvia prompt and temperature transcription options are rejected because this adapter does not map them to xAI.

Model listing

listModels() normalizes inventory but does not classify each model into completion or media types. Keep capability-specific allowlists in application configuration.

Models and media ​

Completion models ​

Image generation ​

Text-to-speech ​