Model Capabilities
Video Generation
Generate videos from text prompts, animate still images, use reference images to guide style and content, edit existing videos, or extend them with natural language. The API supports configurable duration, aspect ratio, and resolution for generated videos — with the SDK handling the asynchronous polling automatically.
Quick Start
Generate a video with a single API call:
import os
import xai_sdk
client = xai_sdk.Client(api_key=os.getenv("XAI_API_KEY"))
response = client.video.generate(
prompt="A glowing crystal-powered rocket launching from the red dunes of Mars, ancient alien ruins lighting up in the background as it soars into a sky full of unfamiliar constellations",
model="grok-imagine-video",
duration=10,
aspect_ratio="16:9",
resolution="720p",
)
print(response.url)
Video generation is an asynchronous process that typically takes up to several minutes to complete. The exact time varies based on:
- Prompt complexity — More detailed scenes require additional processing
- Duration — Longer videos take more time to generate
- Resolution — Higher resolutions (720p vs 480p) increase processing time
- Video editing — Editing existing videos adds overhead compared to image-to-video or text-to-video
How it works
Under the hood, video generation is a two-step process:
- Start — Submit a generation request and receive a
request_id - Poll — Repeatedly check the status using the
request_iduntil the video is ready
The xAI SDK's generate() and extend() methods abstract this entirely — they submit your request, poll for the result, and return the completed video response. You don't need to manage request IDs or implement polling logic. For long-running generations, you can customize the polling behavior with timeout and interval parameters, or handle polling manually for full control over the generation lifecycle.
REST API users must implement this two-step flow manually:
Step 1: Start the generation request
Bash
curl -X POST https://api.x.ai/v1/videos/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $XAI_API_KEY" \
-d '{
"model": "grok-imagine-video",
"prompt": "A glowing crystal-powered rocket launching from Mars"
}'
Response:
JSON
{"request_id": "d97415a1-5796-b7ec-379f-4e6819e08fdf"}
Step 2: Poll for the result
Use the request_id to check the status. Keep polling every few seconds until the video is ready:
Bash
curl -X GET "https://api.x.ai/v1/videos/%7Brequest_id%7D" \
-H "Authorization: Bearer $XAI_API_KEY"
The response includes a status field with one of these values:
| Status | Description |
|---|---|
pending | Video is still being generated |
done | Video is ready |
expired | Request has expired |
failed | Video generation failed |
Response (when complete):
JSON
{
"status": "done",
"video": {
"url": "https://vidgen.x.ai/.../video.mp4",
"duration": 8,
"respect_moderation": true
},
"model": "grok-imagine-video"
}
Videos are returned as temporary URLs. Access the xAI-hosted URL directly when you need it, or download/process it promptly if you need to keep a copy.
Generate Videos from Images
Transform a still image into a video by providing a source image along with your prompt. The model animates the image content based on your instructions.
You can provide the source image as:
- A public URL pointing to an image
- A base64-encoded data URI (e.g.,
data:image/jpeg;base64,...)
The demo below shows this in action — hold to animate a still image:

import osimport xai_sdkclient = xai_sdk.Client(api_key=os.getenv("XAI_API_KEY"))response = client.video.generate( prompt="Generate a slow and serene time-lapse", model="grok-imagine-video", image_url="https://docs.x.ai/assets/api-examples/video/milkyway-still.png", duration=12,)print(response.url)In the Vercel AI SDK, the prompt parameter accepts an object with image and text fields for image-to-video generation. The image field can be a URL string, base64-encoded string, Uint8Array, ArrayBuffer, or Buffer.
Edit Existing Videos
Edit an existing video by providing a source video along with your prompt. The model understands the video content and applies your requested changes.
- The input video must have the
.mp4extension and be encoded with.mp4supported codecs such as H.265 / H.264 / AV1, etc. - The maximum length of the input video provided via the video_url parameter is 8.7 seconds.
- The duration, aspect_ratio, and resolution parameters are not supported for video editing — the output retains the duration and aspect ratio of the input, and matches its resolution (capped at 720p).
The demo below shows video editing in action — grok-imagine-video delivers high-fidelity edits with strong scene preservation, modifying only what you ask for while keeping the rest of the video intact:

import osimport xai_sdkclient = xai_sdk.Client(api_key=os.getenv("XAI_API_KEY"))response = client.video.generate( prompt="Give the woman a silver necklace", model="grok-imagine-video", video_url="https://data.x.ai/docs/video-generation/portrait-wave.mp4",)print(response.url)In the Vercel AI SDK, video editing is triggered by setting providerOptions.xai.mode to "edit-video" and passing providerOptions.xai.videoUrl with a source video URL. The prompt describes the desired modifications; duration, aspectRatio, and resolution are ignored because the output inherits these properties from the input video, capped at 720p.
Generate Videos using Reference Images
Provide one or more reference images to incorporate specific people, objects, clothing, or other visual elements into the generated video. The model uses the reference images as a visual guide, producing a video that features the content from those images — making it ideal for use cases like virtual try-on, product placement, or character-consistent storytelling.
Unlike image-to-video where the source image becomes the starting frame, reference images influence what appears in the video without locking in the first frame.
Each reference image can be provided as a public HTTPS URL or a base64-encoded data URI. In the AI SDK, set providerOptions.xai.mode to "reference-to-video" and pass the images with providerOptions.xai.referenceImageUrls.
- A non-empty
promptis required when using reference images. - A maximum of 7 reference images can be provided per request.
- The maximum
durationallowed when using reference images is 10 seconds. - Reference images cannot be combined with image-to-video or video editing. Only one mode can be active per request, determined by the parameters on the request.
import os
import xai_sdk
client = xai_sdk.Client(api_key=os.getenv("XAI_API_KEY"))
response = client.video.generate(
prompt="slow zoom in on the white fashion runway stage. then, the model from <IMAGE_1> walks in from the back of the shot from the white opening, and gracefully walk out onto the front of the white stage platform. they wear the shirt from <IMAGE_2> and black flared jeans. they look dramatically at the camera. high quality slow motion shot. fun, playful. skin pores. highly detailed faces. perfect shot. they reach the end of the runway and look at the camera as the camera slowly zooms. subtle smile.",
model="grok-imagine-video",
reference_image_urls=[
"<IMAGE_URL_1>",
"<IMAGE_URL_2>",
"<IMAGE_URL_3>",
],
duration=10,
aspect_ratio="16:9",
resolution="720p",
)
print(response.url)
Extend Existing Videos
Extend an existing video by providing a source video and a text prompt describing what should happen next. The result is a single video that picks up seamlessly from the last frame of the input and continues with the generated content.
- The input video must have the
.mp4extension and be encoded with.mp4supported codecs such as H.265 / H.264 / AV1, etc. - The input video duration must be between 2 and 15 seconds.
- The extension duration range is 2–10 seconds (default: 6).
- The aspect_ratio and resolution parameters are not supported for video extension — the output matches the aspect ratio and resolution of the input (capped at 720p).
The duration parameter controls the length of the extended portion only, not the total output. For example, if your input video is 10 seconds and you set duration to 5, the returned video will be 15 seconds long (10s original + 5s extension).
import os
import xai_sdk
client = xai_sdk.Client(api_key=os.getenv("XAI_API_KEY"))
response = client.video.extend(
prompt="The shot pans to an over the shoulder perspective. Calm controlled scene.",
model="grok-imagine-video",
video_url="<VIDEO_URL>",
duration=10,
)
print(response.url)
Video editing uses the /v1/videos/edits endpoint and client.video.generate(video_url=...) in the Python SDK. In the AI SDK, set providerOptions.xai.mode to "edit-video" or "extend-video" and pass providerOptions.xai.videoUrl. The same asynchronous polling pattern applies to both flows, and the AI SDK returns the xAI-hosted output URL in providerMetadata.xai.videoUrl.
Configuration
The video generation API lets you control the output format of your generated videos. You can specify the duration, aspect ratio, and resolution to match your specific use case.
Duration
Control video length with the duration parameter. The allowed range is 1–15 seconds.
Video editing does not support custom duration. The edited video retains the duration of the original, which is capped at 8.7 seconds.
Aspect Ratio
| Ratio | Use case |
|---|---|
1:1 | Social media, thumbnails |
16:9 / 9:16 | Widescreen, mobile, stories (default: 16:9) |
4:3 / 3:4 | Presentations, portraits |
3:2 / 2:3 | Photography |
For image-to-video generation, the output defaults to the input image's aspect ratio. If you specify the aspect_ratio parameter, it will override this and stretch the image to the desired aspect ratio.
Video editing does not support custom aspect_ratio — the output matches the input video's aspect ratio.
Resolution
| Resolution | Description |
|---|---|
720p | HD quality |
480p | Standard definition, faster processing (default) |
Video editing does not support custom resolution. The output resolution matches the input video's resolution, capped at 720p (e.g., a 1080p input will be downsized to 720p).
Example
import os
import xai_sdk
client = xai_sdk.Client(api_key=os.getenv("XAI_API_KEY"))
response = client.video.generate(
prompt="Timelapse of a flower blooming in a sunlit garden",
model="grok-imagine-video",
duration=10,
aspect_ratio="16:9",
resolution="720p",
)
print(f"Video URL: {response.url}")
print(f"Duration: {response.duration}s")
Request Modes
The video generation endpoint supports multiple modes, determined by which fields are set. Only one mode can be active per request:
| Mode | REST API fields | AI SDK shape | Description |
|---|---|---|---|
| Text-to-video | prompt only | prompt: "..." | Generates video from a text prompt alone. |
| Image-to-video | prompt + image | prompt: { image, text } | Generates video with the provided image as the starting frame. |
| Reference-to-video | prompt + reference_images | prompt: "..." + providerOptions.xai.{ mode: "reference-to-video", referenceImageUrls } | Generates video guided by one or more reference images. |
| Edit-video | /v1/videos/edits + video_url | prompt: "..." + providerOptions.xai.{ mode: "edit-video", videoUrl } | Modifies an existing video based on the prompt. |
| Extend-video | /v1/videos/extensions + video | prompt: "..." + providerOptions.xai.{ mode: "extend-video", videoUrl } | Extends an existing video from its last frame. |
The following combination is not allowed and will return a 400 Bad Request error:
image+reference_images— use one or the other- Mixing
modevalues in the AI SDK — each request supports exactly one of"edit-video","extend-video", or"reference-to-video"
When you omit mode, the AI SDK uses standard generation.
Customize Polling Behavior
When using the SDK's generate() or extend() methods, you can control how long to wait and how frequently to check for results:
| Python SDK | AI SDK (providerOptions.xai) | Description | Default |
|---|---|---|---|
timeout | pollTimeoutMs | Maximum time to wait for the video to complete | 10 minutes |
interval | pollIntervalMs | Time between status checks | 100 milliseconds |
import os
from datetime import timedelta
import xai_sdk
client = xai_sdk.Client(api_key=os.getenv("XAI_API_KEY"))
response = client.video.generate(
prompt="Epic cinematic drone shot flying through mountain peaks",
model="grok-imagine-video",
duration=15,
timeout=timedelta(minutes=15), # Wait up to 15 minutes
interval=timedelta(seconds=5), # Check every 5 seconds
)
print(response.url)
If the video isn't ready within the timeout period, the Python SDK raises a TimeoutError and the AI SDK aborts via its AbortSignal. For even finer control, use the manual polling approach — the Python SDK provides start() and get() methods, while the AI SDK supports a custom abortSignal for cancellation.
Handle Polling Manually
For fine-grained control over the generation lifecycle, use start() or extend_start() to initiate generation/extension requests respectively and get() to check status.
The get() method returns a response with a status field. Import the status enum from the SDK:
import os
import time
import xai_sdk
from xai_sdk.proto import deferred_pb2
client = xai_sdk.Client(api_key=os.getenv("XAI_API_KEY"))
# Start the generation request
start_response = client.video.start(
prompt="A cat lounging in a sunbeam, tail gently swishing",
model="grok-imagine-video",
duration=5,
)
print(f"Request ID: {start_response.request_id}")
# Poll for results
while True:
result = client.video.get(start_response.request_id)
if result.status == deferred_pb2.DeferredStatus.DONE:
print(f"Video URL: {result.response.video.url}")
break
elif result.status == deferred_pb2.DeferredStatus.EXPIRED:
print("Request expired")
break
elif result.status == deferred_pb2.DeferredStatus.FAILED:
print("Video generation failed")
break
elif result.status == deferred_pb2.DeferredStatus.PENDING:
print("Still processing...")
time.sleep(5)
The available status values are:
| Proto Value | Description |
|---|---|
deferred_pb2.DeferredStatus.PENDING | Video is still being generated |
deferred_pb2.DeferredStatus.DONE | Video is ready |
deferred_pb2.DeferredStatus.EXPIRED | Request has expired |
deferred_pb2.DeferredStatus.FAILED | Video generation failed |
Error Handling
When using the SDK's generate() or extend() methods, video generation failures are raised as a VideoGenerationError exception. This exception includes a code and message describing what went wrong. Import it from xai_sdk.video:
Python
import os
import xai_sdk
from xai_sdk.video import VideoGenerationError
client = xai_sdk.Client(api_key=os.getenv("XAI_API_KEY"))
try:
response = client.video.generate(
prompt="A cat lounging in a sunbeam, tail gently swishing",
model="grok-imagine-video",
duration=5,
)
print(response.url)
except VideoGenerationError as e:
print(f"Error code: {e.code}")
print(f"Error message: {e.message}")
The VideoGenerationError exception has the following attributes:
| Attribute | Type | Description |
|---|---|---|
code | str | An error code identifying the failure reason |
message | str | A human-readable message describing the failure |
You can combine this with TimeoutError handling for comprehensive error coverage:
Python
import os
import xai_sdk
from xai_sdk.video import VideoGenerationError
client = xai_sdk.Client(api_key=os.getenv("XAI_API_KEY"))
try:
response = client.video.generate(
prompt="A cat lounging in a sunbeam, tail gently swishing",
model="grok-imagine-video",
duration=5,
)
print(response.url)
except VideoGenerationError as e:
print(f"Generation failed [{e.code}]: {e.message}")
except TimeoutError:
print("Generation timed out — try increasing the timeout or simplifying the prompt")
Response Details
The SDK response includes the generated video and provider-specific metadata. In the AI SDK, the xAI-hosted output URL is available at providerMetadata.xai.videoUrl.
if response.respect_moderation:
print(response.url)
else:
print("Video filtered by moderation")
print(f"Duration: {response.duration} seconds")
print(f"Model: {response.model}")
Concurrent Requests
When you need to generate multiple videos or apply several edits to the same source video, run requests concurrently. This is especially useful for branching multiple edits from the same intermediate result.
The examples below show both Python concurrency and the AI SDK pattern for chaining one edit into concurrent follow-up edits.
import os
import asyncio
import xai_sdk
async def edit_concurrently():
client = xai_sdk.AsyncClient(api_key=os.getenv("XAI_API_KEY"))
source_video = "https://data.x.ai/docs/video-generation/portrait-wave.mp4"
prompts = [
"Give the woman a silver necklace",
"Change the color of the woman's outfit to red",
"Give the woman a wide-brimmed black hat",
]
tasks = [
client.video.generate(
prompt=prompt,
model="grok-imagine-video",
video_url=source_video,
)
for prompt in prompts
]
results = await asyncio.gather(*tasks)
for prompt, result in zip(prompts, results):
print(f"{prompt}: {result.url}")
asyncio.run(edit_concurrently())
Pricing
Video generation uses per-second pricing. Longer videos cost more, and both duration and resolution affect the total cost.
For full pricing details on the grok-imagine-video model, see the model page.
Limitations
- Maximum duration: 15 seconds for generation, 8.7 seconds for editing input videos, 2–10 seconds for video extensions (input video must be 2–15 seconds)
- URL expiration: Generated URLs are ephemeral and should not be relied upon for long-term storage
- Resolutions: 480p or 720p
- Content moderation: Videos are subject to content policy review
Related
- Models — Available video models and pricing
- Image Generation — Generate still images from text
- API Reference — Full endpoint documentation
- Imagine API Landing Page — Showcase of the Imagine API in action
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Last updated: April 2, 2026