Train and Deploy Video LoRAs with LTX

The first open-source video generation model built for LoRA fine-tuning. Train custom characters, styles, and motion, then run locally on-prem.

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Key Capabilities

  • Video-native LoRA training

    Fine-tune on characters, styles, or motion patterns. LTX is built for video from the ground up, not an image model with video bolted on.
  • Character consistency with IC-LoRA

    Train in-context characters that maintain appearance across scenes and generations, making it reliable for any production use case that requires visual continuity.
  • Deploy anywhere

    Load trained LoRAs into ComfyUI workflows or access curated LoRA-powered endpoints on fal.ai and Replicate. Weights are open-source on Hugging Face and integrate into your existing pipeline.

Fine-tune LTX with LoRAs

Train a lightweight LoRA adapter on your own reference material to generate videos with custom characters, branded styles, or specific motion patterns. LTX LoRA training runs on video data natively, not image frames, so output reflects real motion and temporal consistency from the start.

Consistent characters across every generation

IC-LoRA trains a character identity from reference images, then generates videos where that character holds its appearance across scenes, angles, and lighting. The same face, the same features, across every output.

Train custom styles and motion

LoRA training goes beyond character faces. Train branded visual styles including color palettes, lighting, and grain. Define specific motion patterns like camera movements and animation styles. Control how your product or subject looks and moves across every generation.

Deploy via API or ComfyUI

Train a LoRA, then run it via ComfyUI, self-host it locally, or access LoRA-powered endpoints on fal.ai and Replicate. Your weights are yours to export or share. No lock-in, no closed ecosystem.

How LoRA training works

Input:

  • Training data (required) β€” 10 to 50 reference images or short video clips of your subject or style.
  • Text captions (optional) β€” Describe each reference to guide training alignment.
  • Training parameters β€” LoRA rank, learning rate, epochs, batch size.
  • Supported formats β€” PNG, JPEG, WEBP, MP4.‍
  • Training methods β€” Standard LoRA, IC-LoRA (in-context).

Output:

  • LoRA weights file β€” Compatible with Hugging Face diffusers and ComfyUI.
  • Deployment options β€” ComfyUI workflow, local inference, fal.ai and Replicate endpoints.
  • Consistency β€” Maintains trained subject and style across generations.
  • Combinable β€” Merge multiple LoRAs (character plus style) at inference time.
  • Open weights β€” You own your trained LoRA. Export, share, or self-host.

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Designed for real-world deployment

Production-ready LoRA training for enterprise teams building scalable, controllable video generation workflows.

Builders

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.

Producers at scale

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.

On-prem operators

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.

Platform teams

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 LoRA training works

Input

Train a custom LoRA adapter by providing reference material: images, video clips, or both, that represent your target character, style, or motion.

Technical characteristics:

  • Training data (required) β€” 10 to 50 reference images or short video clips of your subject or style.
  • Text captions (optional) β€” Describe each reference to guide training alignment.
  • Training parameters β€” LoRA rank, learning rate, epochs, batch size.
  • Supported formats β€” PNG, JPEG, WEBP, MP4.‍
  • Training methods β€” Standard LoRA, IC-LoRA (in-context).

Output

A lightweight LoRA weights file that loads into LTX at inference time via ComfyUI or a local pipeline to generate videos with your trained character, style, or motion.

Technical characteristics:

  • LoRA weights file β€” Compatible with Hugging Face diffusers and ComfyUI.
  • Deployment options β€” ComfyUI workflow, local inference, fal.ai and Replicate endpoints.
  • Consistency β€” Maintains trained subject and style across generations.
  • Combinable β€” Merge multiple LoRAs (character plus style) at inference time.
  • Open weights β€” You own your trained LoRA. Export, share, or self-host.

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Retake - Video Editing

LTX-2.3
Pro

Refine only the parts that need adjustment - no need to regenerate the whole video. Perfect for fixing scenes, adjusting elements, or improving localized areas.

URL path:
/v1/retake
Pricing:
  • 1920Γ—1080 β€” $0.10/sec
Notes:
  • Currently available in 1080p only.
  • Billed per second of input video.

Text-to-Video

LTX-2.3
Pro

Optimized for higher fidelity and increased temporal stability. Best for production-ready output and final renders.

URL path:
/v1/text-to-video
Pricing:
  • 1920Γ—1080 β€” $0.08/sec
  • 2560Γ—1440 β€” $0.16/sec
  • 3840Γ—2160 β€” $0.32/sec
Notes:
  • Deal for client-facing content or polished deliverables.
  • Higher compute level β†’ higher visual quality.