Install
openclaw skills install grok-imagine-imageGenerate images with xAI Grok Imagine models — batch generation, aspect ratios, base64 output, concurrent requests. Use when user wants AI image generation via xAI API.
openclaw skills install grok-imagine-imageGenerate images from text with Grok Imagine models. Supports batch, aspect ratio, resolution, base64, and concurrent requests.
curl -X POST https://api.x.ai/v1/images/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $XAI_API_KEY" \
-d '{
"model": "grok-imagine-image-quality",
"prompt": "A futuristic city skyline at night"
}'
| Model | Status | Use Case |
|---|---|---|
grok-imagine-image-quality | ✅ Current | All new requests |
grok-imagine-image-pro | ⚠️ Deprecated May 2026 | Legacy, migrate to quality |
prompt (required) — Text descriptionmodel (required) — grok-imagine-image-qualityn (optional) — Number of images (1-4)response_format (optional) — url (default) or b64_jsoncurl -X POST https://api.x.ai/v1/images/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $XAI_API_KEY" \
-d '{
"model": "grok-imagine-image-quality",
"prompt": "A collage of London landmarks in stenciled street-art style"
}'
curl -X POST https://api.x.ai/v1/images/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $XAI_API_KEY" \
-d '{
"model": "grok-imagine-image-quality",
"prompt": "A futuristic city skyline at night",
"n": 4
}'
curl -X POST https://api.x.ai/v1/images/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $XAI_API_KEY" \
-d '{
"model": "grok-imagine-image-quality",
"prompt": "A serene Japanese garden",
"response_format": "b64_json"
}'
{
"data": [
{
"url": "https://...",
"b64_json": "..."
}
]
}
import xai_sdk
client = xai_sdk.Client()
response = client.image.sample(
prompt="A futuristic city skyline",
model="grok-imagine-image-quality",
)
print(response.url)
from openai import OpenAI
client = OpenAI(
base_url="https://api.x.ai/v1",
api_key="YOUR_XAI_API_KEY",
)
response = client.images.generate(
model="grok-imagine-image-quality",
prompt="A futuristic city skyline",
)
print(response.data[0].url)
b64_json for embeddingn parameter for batch variationsrespect_moderation for content filtering