Image Generation
Last updated January 21, 2026
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 2.5 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 apiKey = process.env.AI_GATEWAY_API_KEY || process.env.VERCEL_OIDC_TOKEN;
const openai = new OpenAI({
apiKey,
baseURL: 'https://ai-gateway.vercel.sh/v1',
});
const completion = await openai.chat.completions.create({
model: 'google/gemini-2.5-flash-image-preview',
messages: [
{
role: 'user',
content:
'Generate a beautiful sunset over mountains and describe the scene.',
},
],
// @ts-expect-error - modalities not yet in OpenAI types but supported by gateway
modalities: ['text', 'image'],
stream: false,
});
const message = completion.choices[0].message;
// Text content is always a string
console.log('Text:', message.content);
// Images are in a separate array
if (message.images && Array.isArray(message.images)) {
console.log(`Generated ${message.images.length} images:`);
for (const [index, img] of message.images.entries()) {
if (img.type === 'image_url' && img.image_url) {
console.log(`Image ${index + 1}:`, {
size: img.image_url.url?.length || 0,
preview: `${img.image_url.url?.substring(0, 50)}...`,
});
}
}
}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-2.5-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}')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-2.5-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
}
}content: Contains the text description as a stringimages: Array of generated images, each with:type: Always"image_url"image_url.url: Base64-encoded data URI of the generated image
For streaming requests, images are delivered in delta chunks:
{
"id": "chatcmpl-123",
"object": "chat.completion.chunk",
"created": 1677652288,
"model": "google/gemini-2.5-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
}
]
}When processing streaming responses, check for both text content and images in each delta:
streaming-images.ts
import OpenAI from 'openai';
const openai = new OpenAI({
apiKey: process.env.AI_GATEWAY_API_KEY,
baseURL: 'https://ai-gateway.vercel.sh/v1',
});
const stream = await openai.chat.completions.create({
model: 'google/gemini-2.5-flash-image-preview',
messages: [{ role: 'user', content: 'Generate a sunset image' }],
// @ts-expect-error - modalities not yet in OpenAI types
modalities: ['text', 'image'],
stream: true,
});
for await (const chunk of stream) {
const delta = chunk.choices[0]?.delta;
// Handle text content
if (delta?.content) {
process.stdout.write(delta.content);
}
// Handle images
if (delta?.images) {
for (const img of delta.images) {
if (img.type === 'image_url' && img.image_url) {
console.log(`\n[Image received: ${img.image_url.url.length} chars]`);
}
}
}
}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-2.5-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 support: Currently, image generation is supported by Google's Gemini 2.5 Flash Image model. The generated images are returned as base64-encoded data URIs in the response. For more detailed information about image generation capabilities, see the Image Generation documentation.
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