AI Text-to-Video Model
Language defines the video. Prompts control motion, composition, and visual flow.
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Key Capabilities
Prompt-driven generation
Video is generated from text prompts, with language controlling actions, camera movement, environments, visual style, and motion.
Cinematic output
Professional-grade visual quality at native 4K, up to 50 FPS. Built for cinematic motion and visual clarity, not low-res demos.
Production-ready performance
Optimized inference pipelines, stable API deployment, and predictable behavior. Suitable for rapid iteration and enterprise-scale deployment.
Content creation without manual animation
Generate videos directly from text descriptions for storytelling, creative exploration, and concept development. No keyframing required.
Marketing & brand content
Produce promotional videos, product scenes, and branded content from text descriptions. Fast iteration, repeatable results, and scalable production.
Previsualization & storyboarding
Translate scripts and shot descriptions into video previews to explore narrative flow, pacing, and framing choices before committing to production.
Research & model experimentation
Study prompt adherence, temporal reasoning, and generative behavior with a production-grade text-to-video foundation model.
How it works
Input:
- Text prompt (required): Detailed description of actions, scenes, camera behavior, and visual style
- Optional conditioning: Images or keyframes to anchor composition or layout
- Generation parameters: Resolution, FPS, duration, seed, inference steps
Output:
- MP4 video generated from text
- Up to ~20 seconds per generation
- Coherent motion, style consistency, and prompt-aligned structure
How it works
Input
Describe the scene you want to generate using a detailed text prompt. Optionally add visual conditioning to control actions, camera movement, layout, and overall style.
Technical characteristics:
- Text prompt (required): Detailed description of actions, scenes, camera behavior, and visual style
- Optional conditioning: Images or keyframes to anchor composition or layout
- Generation parameters: Resolution, FPS, duration, seed, inference steps
Output
Receive an MP4 video generated from your text prompt, with coherent motion, consistent visuals, and structure aligned to your described scene.
Technical characteristics:
- MP4 video generated from text
- Up to ~20 seconds per generation
- Coherent motion, style consistency, and prompt-aligned structure
Text to Video Pricing
Text-to-Video
Designed for quick iteration, previews, and fast creative exploration.
- 1920×1080 — $0.04/sec
- 2560×1440 — $0.08/sec
- 3840×2160 (4K) — $0.16/sec
- Same pricing applies for text input and pure prompt -based generation.
Text-to-Video
Optimized for higher fidelity and increased temporal stability. Best for production-ready output and final renders.
- 1920×1080 — $0.06/sec
- 2560×1440 — $0.12/sec
- 3840×2160 (4K) — $0.24/sec
- Deal for client-facing content or polished deliverables.
- Higher compute level → higher visual quality.
About LTX Models
LTX builds state-of-the-art generative AI models designed for real-world deployment. Our models prioritize control, composability, and performance — enabling developers and platforms to build production-ready AI video experiences.
Personas
Subtext goes here enables true audio-to-video AI generation without relying on text-first pipelines.
Product integrators
Embed video generation into existing platforms with minimal engineering overhead. Reliable API, predictable performance, easy integration.
Visionaries & custom builders
Build and fine-tune video products on a stable foundation. High-fidelity outputs and long-term model stability for vertical AI solutions.
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Enterprise Content Platforms
Transform voice, music, and sound into high-quality video for campaigns, education, and distribution pipelines.
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Research & Academia
Experiment with audio-driven animation, timing alignment, and audio-visual generation using a controllable video model.
Persona 5
Experiment with audio-driven animation, timing alignment, and audio-visual generation using a controllable video model.
Persona 6
Experiment with audio-driven animation, timing alignment, and audio-visual generation using a controllable video model.
Persona 7
Experiment with audio-driven animation, timing alignment, and audio-visual generation using a controllable video model.
Persona 8
Experiment with audio-driven animation, timing alignment, and audio-visual generation using a controllable video model.
FAQs
What is the Text-to-Video model in LTX?
An AI video generation model that produces video directly from text prompts. Language conditions motion, composition, and visual flow.
How does LTX-2's Text-to-Video work?
The model interprets detailed text prompts—actions, scenes, camera movement, style—and translates them into coherent video sequences with consistent motion and structure.
How is LTX-2 different from other text-to-video models?
Built for cinematic quality and production workflows, not demos. High-resolution output, strong prompt adherence, and scalable inference for real-world deployment.
What video quality can I expect?
High-fidelity generation with native 4K output and high frame rates. Smooth motion and professional-grade visual quality.
How long can videos be?
Up to ~20 seconds per generation. Longer sequences through chained generations and composable workflows.
Can I control camera movement through text?
Yes. Prompts specify camera angles, movement, pacing, transitions, lighting, and scene dynamics. Fine-grained control through language alone.
Is text-to-video available via API?
Yes. Available through the LTX-2 API, designed for developers, platforms, and enterprise teams integrating video generation into products.
Is the LTX-2 Text-to-Video model open source?
Yes. Code and model weights available on GitHub and Hugging Face. Inspect, run locally, fine-tune, and integrate into custom workflows.
Can text-to-video combine with images or keyframes?
Yes. Hybrid workflows where text prompts work alongside images or keyframes to anchor composition, maintain continuity, or guide structure.
Is LTX-2 suitable for production?
Yes. Built for predictable behavior, high-quality output, and scalable deployment in real-world production environments.
