Grok Imagine Video
Grok Imagine Video is xAI’s high‑fidelity video generation model that creates short clips with synchronized audio from text or image inputs.
What is Grok Imagine Video?
Grok Imagine Video is a video generation model from xAI that produces short, high‑quality clips, often with native synchronized audio, from text, images, or existing video. It is mainly used for text‑to‑video and image‑to‑video generation to create cinematic scenes, character animations, and visually rich promo or social content. It is also used to extend or edit existing videos, add motion and sound to still images, and prototype storyboards and music videos. The model is part of the broader Grok Imagine family built on xAI’s Aurora autoregressive video architecture.
Providers
Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Exacto (highest tool-calling accuracy).
| Provider | Input | Output | Cache read /M | Latency | Throughput | Uptime |
|---|---|---|---|---|---|---|
| xAI | ~$0.12/vid | ~$0.00/vid | — | ~3.5s | ~18 vid/min | ~99.9% |
| OpenAI | ~$0.15/vid | ~$0.00/vid | — | ~3.8s | ~16 vid/min | 99.06% |
| Google Cloud | ~$0.14/vid | ~$0.00/vid | — | ~4.0s | ~15 vid/min | 99.9% |
| Azure AI | ~$0.16/vid | ~$0.00/vid | — | ~4.2s | ~14 vid/min | 100.00% |
Try this model
Test Grok Imagine Video right here — free to start.
Suggestions for your first prompt
Code snippet
Call the model through the OpenAI-compatible API.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://inference.example.com/v1"
)
response = client.chat.completions.create(
model="xai/grok-imagine-video",
messages=[
{
"role": "user",
"content": "Describe this image in one sentence."
}
],
)
print(response.to_json())
{
"model": "xai/grok-imagine-video",
"messages": [
{
"role": "user",
"content": "Describe this image in one sentence."
}
]
}
5 Core Capabilities
-
Text-to-video generation
Generates short-form videos from natural-language prompts, creating coherent scenes, motion, and synchronized audio up to around 15 seconds.
-
Image-to-video animation
Animates one or multiple reference images into a coherent video clip, preserving character identity and visual style across frames.
-
Multimodal input handling
Accepts text, image, and video as inputs, enabling flexible video generation and extension workflows through a unified autoregressive engine.
-
Video extension editing
Extends existing clips by adding new segments, allowing iterative refinement and longer sequences while maintaining temporal and visual consistency.
-
Audio-synchronized output
Produces videos with native audio tracks, including ambient sound, music, or dialogue that match the generated visual content.
6 Most Valuable Use Cases
- Marketing Video Generation
- Product Demo Videos
- Educational Explainer Clips
- Social Media Content
- Advertising Storyboards
- AI Video Prototyping
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
-
Unified AI Routing
Automatically route each request to the optimal model across providers based on performance, latency, and cost. One endpoint, dynamic policies, no SDK sprawl.
One endpoint, every model -
Cost-Aware Control
Set smart cost policies per route, workspace, or feature. Mix premium and budget models while keeping strict spend guardrails and clear unit economics.
Cut spend, keep quality -
Resilient Fallbacks
Define automatic failover chains when models error, time out, or degrade. Keep your AI features online without custom retry logic or provider lock‑in.
No single point of failure -
Deep Observability
Track latency, tokens, cost, and errors across all providers in one place. Correlate issues to routes and experiments with production-grade telemetry.
See every call, instantly -
Task-Level Orchestration
Express multi-step AI workflows as tasks with built-in retries, dependencies, and tools. Ship complex agents without wiring custom orchestration infrastructure.
From prompts to workflows -
High-Throughput Batch
Submit massive batch jobs across providers with queueing, parallelism controls, and automatic retries. Optimize throughput and cost for large offline workloads.
Scale jobs, not servers
When to Use — When NOT to Use
Use it if...
- You need to generate short, eye-catching marketing videos from text prompts or scripts.
- Your use case involves creating quick video concepts or storyboards for creative ideation.
- You need AI-generated video clips to complement social media campaigns and announcements.
- Your use case involves experimenting with cutting-edge text-to-video models from the xAI ecosystem.
- You need visually engaging demos or prototypes without hiring full video production teams.
- Your use case involves creating illustrative videos where roughness is acceptable over cinematic polish.
Avoid if...
- You need precise control over shot composition, camera paths, and frame-by-frame editing.
- Your workload requires highly photorealistic, production-grade video for film or television releases.
- You need guaranteed consistent character appearance across long multi-scene narrative videos.
- Your workload requires strict content filters and enterprise-grade compliance certifications already well documented.
- You need deterministic, reproducible outputs where small prompt changes never significantly alter results.
- Your workload requires on-premise deployment or offline generation without cloud-based dependencies.
Frequently Asked Questions
-
What is Grok Imagine Video?
Grok Imagine Video is an xAI generative model that creates videos from text prompts, optimized for fast iteration and developer-focused integration.
-
Which modalities does Grok Imagine Video support via LLM.API?
Grok Imagine Video currently supports text-to-video generation and may also accept image-plus-text prompts depending on the specific LLM.API route configuration.
-
How is Grok Imagine Video priced on LLM.API?
Grok Imagine Video is billed per generated video or per compute unit, with exact pricing defined in the LLM.API Grok Imagine Video pricing table.
-
What is the context window of Grok Imagine Video?
Grok Imagine Video accepts prompts up to the maximum token or character limits documented for its endpoint in the LLM.API reference.
-
How fast is Grok Imagine Video when generating videos?
Grok Imagine Video typically has higher latency than text models, with generation time depending on video duration, resolution, and load on LLM.API infrastructure.
-
How do I access Grok Imagine Video through LLM.API?
You call the standard LLM.API generation endpoint with the model identifier for Grok Imagine Video and provide your text prompt plus optional video parameters.
-
How does Grok Imagine Video compare to other video generation models on LLM.API?
Grok Imagine Video emphasizes rapid iteration, on-brand stylistic control, and xAI ecosystem compatibility compared with more general-purpose or research-focused video generators.
-
What are the main limitations of Grok Imagine Video?
Grok Imagine Video can struggle with fine-grained text rendering, complex physics, long coherent narratives, and may produce artifacts or temporally inconsistent frames.
-
Can Grok Imagine Video generate audio or soundtracks with its videos?
By default, Grok Imagine Video produces silent video clips, and any audio must be added separately unless LLM.API specifies combined audio-video support.
-
Are there safety or content restrictions when using Grok Imagine Video on LLM.API?
Yes, Grok Imagine Video requests are filtered by LLM.API and xAI safety policies, which restrict disallowed content such as explicit, violent, or illegal material.
Get one key to every model
Swap your API key. Keep your code.