AI image to video model
Generate high-quality video from a single image or multiple keyframes, built for control, consistency, and scale.
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Key capabilities
Consistent motion from a single image
Turn a still image into a smooth, natural video while keeping the subject stable and visually consistent across frames.
Multi-keyframe control
Define key moments using multiple images to guide motion, transitions, and scene structure with precision.
Animate still images
Turn a single image into dynamic video with natural motion and camera movement, ideal for artwork, photography, and product visuals.
Marketing & product visuals
Create short videos from static product images for ads, social content, and brand storytelling at scale.
Character & scene animation
Animate illustrated characters or environments while preserving identity, style, and composition across frames.
Storyboarding & visual ideation
Explore motion, pacing, and framing by animating concept art or reference images before full production.
Designed for real-world deployment
A production-ready image-to-video AI model for teams building scalable, controllable video generation workflows.
Product teams, AI startups, and developers building AI-powered video features. Add production-grade video generation as a product capability, not a research project. One API, production-ready results, and no custom orchestration.
Brands, agencies, and creative teams producing high volumes of content. Turn existing assets into video at scale. Faster iteration, lower production cost, and more output from what you already have.
Teams that require full control over deployment and data. Run video generation in your own environment. On-premises, no cloud dependency, and full infrastructure ownership.
Platforms powering creative tools with multiple AI models. Upgrade your video output with a best-in-class engine. Improve generation quality, retain users, and differentiate with a model built for production, not prototypes.
How the Image to Video model works
Input
Provide a source image as your visual anchor. Optionally add a text prompt to guide motion, camera behavior, and style.
Technical characteristics:
- Image (required): Single image or multiple images used as keyframes
- Optional text prompt: Guides motion, camera behavior, and visual style
- Optional parameters: Resolution, FPS, duration, seed, inference steps
- Supported formats: PNG, JPEG/JPG, WEBP
Output
Receive an MP4 video animated from your image, with natural motion and camera movement while the original subject and visual identity are preserved.
Technical characteristics:
- MP4 video generated from image input
- Up to ~20 seconds per generation
- Coherent motion, identity preservation, and prompt-aligned style when a prompt is provided
Image-to-Video
For detailed, stable motion derived from a still image. Best for high-quality sequences, storytelling, and production use.
- 1280×720 — $0.04/sec
- 1920×1080 — $0.08/sec
- 2560×1440 — $0.16/sec
- 3840×2160 — $0.32/sec
- Uses the Pro rendering path for maximum fidelity.
- Ideal when visual consistency is critical.
Image-to-Video
For detailed, stable motion derived from a still image. Best for high-quality sequences, storytelling, and production use.
- 1280×720 — $0.12/sec
- 1920×1080 — $0.17/sec
- 2560×1440 — $0.25/sec
- 3840×2160 — $0.39/sec
- Uses the Pro rendering path for maximum fidelity.
- Ideal when visual consistency is critical.
What users are building with LTX
FAQs
What is the Image to Video model in LTX?
The LTX Image to Video model is an AI video generation model that creates video from static images, using visual input as the primary conditioning signal to generate motion, structure, and temporal continuity.
How does the LTX Image to Video model work?
The LTX Image to Video model generates video by conditioning on one or more images, optionally guided by text prompts. Images define composition and identity, while the model synthesizes coherent motion across frames.
Is the LTX Image to Video model open source?
Yes. The LTX Image to Video model is open source, with code and model weights available on GitHub and Hugging Face. This allows developers and researchers to run the model locally, inspect the implementation, fine-tune it, and integrate it deeply into custom pipelines.
How can I improve motion quality when generating video from images?
Motion quality can be improved by:
- Using detailed prompts that describe movement and camera behavior
- Adjusting conditioning strength
- Using preprocessing and control workflows
- Leveraging official ComfyUI pipelines and examples
These approaches help avoid static motion or simple zoom effects.
Can I use multiple images or keyframes?
Yes. The LTX Image to Video model supports multi-image and keyframe conditioning, allowing you to guide structure, transitions, and scene evolution using multiple visual references.
Does the Image to Video model support pose, depth, or edge control?
Yes. Image to Video workflows can be guided using control LoRAs (such as pose, depth, and canny), enabling more structured and controllable motion from static images.
Is the LTX Image to Video model available via API?
Yes. The LTX Image to Video model is available via a production-ready API as part of LTX Models, enabling scalable integration into products and platforms.
