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AI Gateway Chat Completions Image Generation Reference

Generate images using AI models that support multimodal output through the Chat Completions API. This feature allows you to create images alongside text responses using models like Google's Gemini 3.1 Flash Image.

Endpoint
POST /chat/completions
Parameters

To enable image generation, include the modalities parameter in your request:

  • modalities (array): Array of strings specifying the desired output modalities. Use ['text', 'image'] for both text and image generation, or ['image'] for image-only generation.
Example requests
image-generation.ts
import OpenAI from 'openai';
 
const client = new OpenAI({
  apiKey: process.env.AI_GATEWAY_API_KEY,
  baseURL: 'https://ai-gateway.vercel.sh/v1',
});
 
type ImageOutput = { images?: Array<{ image_url: { url: string } }> };
 
const completion = await client.chat.completions.create({
  model: 'google/gemini-3.1-flash-image-preview',
  messages: [{ role: 'user', content: 'Generate a sunset image and describe it.' }],
  // @ts-expect-error AI Gateway supports image output beyond OpenAI's text/audio types.
  modalities: ['text', 'image'],
  stream: false,
});
 
const message = completion.choices[0].message as
  OpenAI.Chat.Completions.ChatCompletionMessage & ImageOutput;
console.log(message.content);
for (const image of message.images ?? []) {
  console.log('Image:', image.image_url.url);
}
image-generation.py
import os
from openai import OpenAI
 
api_key = os.getenv('AI_GATEWAY_API_KEY') or os.getenv('VERCEL_OIDC_TOKEN')
 
client = OpenAI(
    api_key=api_key,
    base_url='https://ai-gateway.vercel.sh/v1'
)
 
completion = client.chat.completions.create(
    model='google/gemini-3.1-flash-image-preview',
    messages=[
        {
            'role': 'user',
            'content': 'Generate a beautiful sunset over mountains and describe the scene.'
        }
    ],
    # Note: modalities parameter is not yet in OpenAI Python types but supported by our gateway
    extra_body={'modalities': ['text', 'image']},
    stream=False,
)
 
message = completion.choices[0].message
 
# Text content is always a string
print(f"Text: {message.content}")
 
# Images are in a separate array
if hasattr(message, 'images') and message.images:
    print(f"Generated {len(message.images)} images:")
    for i, img in enumerate(message.images):
        if img.get('type') == 'image_url' and img.get('image_url'):
            image_url = img['image_url']['url']
            data_size = len(image_url) if image_url else 0
            print(f"Image {i+1}: size: {data_size} chars")
            print(f"Preview: {image_url[:50]}...")
 
print(f'Tokens used: {completion.usage}')
image-generation.sh
curl -X POST "https://ai-gateway.vercel.sh/v1/chat/completions" \
  -H "Authorization: Bearer $AI_GATEWAY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "google/gemini-3.1-flash-image-preview",
    "messages": [
      {
        "role": "user",
        "content": "Generate a beautiful sunset over mountains and describe the scene."
      }
    ],
    "modalities": [
      "text",
      "image"
    ],
    "stream": false
  }'
Response format

When image generation is enabled, the response separates text content from generated images:

{
  "id": "chatcmpl-123",
  "object": "chat.completion",
  "created": 1677652288,
  "model": "google/gemini-3.1-flash-image-preview",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Here's a beautiful sunset scene over the mountains...",
        "images": [
          {
            "type": "image_url",
            "image_url": {
              "url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8/5+hHgAHggJ/PchI7wAAAABJRU5ErkJggg=="
            }
          }
        ]
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 15,
    "completion_tokens": 28,
    "total_tokens": 43
  }
}

Response structure details

  • content: Contains the text description as a string
  • images: Array of generated images, each with:
    • type: Always "image_url"
    • image_url.url: Base64-encoded data URI of the generated image

Streaming responses

For streaming requests, images are delivered in delta chunks:

{
  "id": "chatcmpl-123",
  "object": "chat.completion.chunk",
  "created": 1677652288,
  "model": "google/gemini-3.1-flash-image-preview",
  "choices": [
    {
      "index": 0,
      "delta": {
        "images": [
          {
            "type": "image_url",
            "image_url": {
              "url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8/5+hHgAHggJ/PchI7wAAAABJRU5ErkJggg=="
            }
          }
        ]
      },
      "finish_reason": null
    }
  ]
}

Handling streaming image responses

When processing streaming responses, check for both text content and images in each delta:

streaming-images.ts
import OpenAI from 'openai';
 
const client = new OpenAI({
  apiKey: process.env.AI_GATEWAY_API_KEY,
  baseURL: 'https://ai-gateway.vercel.sh/v1',
});
 
type ImageOutput = { images?: Array<{ image_url: { url: string } }> };
 
const stream = await client.chat.completions.create({
  model: 'google/gemini-3.1-flash-image-preview',
  messages: [{ role: 'user', content: 'Generate a sunset image and describe it.' }],
  // @ts-expect-error AI Gateway supports image output beyond OpenAI's text/audio types.
  modalities: ['text', 'image'],
  stream: true,
});
 
for await (const chunk of stream) {
  const delta = chunk.choices[0]?.delta as
    | (OpenAI.Chat.Completions.ChatCompletionChunk.Choice.Delta & ImageOutput)
    | undefined;
  if (delta?.content) process.stdout.write(delta.content);
  for (const image of delta?.images ?? []) {
    console.log('Image:', image.image_url.url);
  }
}
streaming-images.py
import os
from openai import OpenAI
 
client = OpenAI(
    api_key=os.getenv('AI_GATEWAY_API_KEY'),
    base_url='https://ai-gateway.vercel.sh/v1'
)
 
stream = client.chat.completions.create(
    model='google/gemini-3.1-flash-image-preview',
    messages=[{'role': 'user', 'content': 'Generate a sunset image'}],
    extra_body={'modalities': ['text', 'image']},
    stream=True,
)
 
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta:
        delta = chunk.choices[0].delta
 
        # Handle text content
        if hasattr(delta, 'content') and delta.content:
            print(delta.content, end='', flush=True)
 
        # Handle images
        if hasattr(delta, 'images') and delta.images:
            for img in delta.images:
                if img.get('type') == 'image_url' and img.get('image_url'):
                    image_url = img['image_url']['url']
                    print(f"\n[Image received: {len(image_url)} chars]")
image-generation-stream.sh
curl -X POST "https://ai-gateway.vercel.sh/v1/chat/completions" \
  -H "Authorization: Bearer $AI_GATEWAY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "google/gemini-3.1-flash-image-preview",
    "messages": [
      {
        "role": "user",
        "content": "Generate a sunset image"
      }
    ],
    "modalities": [
      "text",
      "image"
    ],
    "stream": true
  }'

Image-only models (different endpoint)

OpenAI's openai/gpt-image-2 and other image-only models (for example, Flux, Recraft, Grok Imagine) do not accept the Chat Completions modalities parameter. They use the OpenAI-compatible Images endpoint (/v1/images/generations) instead of /v1/chat/completions, called via openai.images.generate.

See the image-only models examples for openai/gpt-image-2, Flux, and Grok Imagine.

To edit an existing image with these models, use the /v1/images/edits endpoint (openai.images.edit). See editing images.

Image generation support: Multimodal image output through Chat Completions modalities is supported by Google's Gemini 2.5 Flash Image. Generated images are returned as base64-encoded data URIs. For more detail, see the Image Generation documentation.

Last updated September 8, 2026
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