Worldwide
2026
Media & Entertainment, Film Production, Advertising, Marketing, Creative Technology, Video Production
LTX Lab is an artificial intelligence research and development organization focused on generative video and world models. Its work centers on the LTX family of models, which generate synchronized visual and audio content from text, images, video, and audio inputs. The current LTX-2.5 system combines video and audio generation within a single model architecture and is available through hosted APIs as well as open weights for local execution and customization.
LTX Lab develops AI models and infrastructure for generating and manipulating video. Its technology supports text-to-video, image-to-video, and audio-to-video generation, allowing developers and creative teams to turn prompts or source media into generated video sequences.
The lab also makes its models available for developers through an API and for local deployment through open model weights. LTX-2.5 can be integrated into custom pipelines or used with ComfyUI workflows, giving developers options for local execution, fine-tuning, and workflow customization. Its models are designed for use in creative production processes where control over motion, visual consistency, audio, duration, and output resolution is important.
LTX Lab’s current technology centers on LTX-2.5, an open-weight generative world model built around a diffusion-transformer architecture. The model can generate synchronized video and audio and accepts text, image, video, and audio as conditioning inputs.
A major capability is native multi-shot generation. Instead of treating each shot as an isolated generation, LTX-2.5 can produce connected shots while maintaining elements such as characters, scenes, lighting, visual style, and voice across cuts. Its architecture also includes a diffusion video decoder intended to improve fine details, facial rendering, typography, product elements, and stability during motion.
The model uses a custom Gemma 4 12B text encoder for prompt conditioning and supports automatic duration, allowing the system to determine an appropriate clip length from the requested action. LTX-2.5 also supports LoRA and IC-LoRA customization for controlling elements such as style, motion, and structure. Developers can run the model through native Python pipelines or ComfyUI-based workflows.
LTX Lab is relevant to the development of open generative video models because its technology combines video generation, synchronized audio, multi-shot sequencing, and developer access within the same model ecosystem. LTX-2.5 can be run locally and fine-tuned rather than being limited to a closed hosted service.
Its work also reflects a broader shift from AI systems that generate isolated short clips toward controllable AI video production workflows. Native multi-shot generation, audio synchronization, first/last-frame controls, and higher-resolution output give developers more building blocks for incorporating generative video into filmmaking, advertising, media production, and creative software.
LTX-2.5 is the lab’s current generative video and audio model. It is offered in Fast and Pro variants and supports text-to-video, image-to-video, and audio-to-video generation. Both variants support portrait and landscape output up to 4K, while features include camera-motion controls, automatic duration, and first/last-frame conditioning for supported workflows.
The open version of LTX-2.5 provides open model weights for local execution and fine-tuning. Developers can work with the model through ComfyUI or native Python pipelines. The open model supports synchronized audio and video generation along with LoRA and IC-LoRA customization.
The LTX API provides developers with programmatic access to the company’s video-generation models. Current endpoints support text-to-video, image-to-video and audio-to-video, while LTX-2.3 additionally supports operations such as retake, extend, and reframe. The API supports multiple resolutions and cinematic frame rates depending on the selected model.
LTX Lab’s technology is primarily applicable to film, video production, advertising, and digital content creation. Text-to-video can generate scenes directly from descriptions, while image-to-video can animate reference imagery and first/last-frame controls can guide how a sequence begins and ends.
Audio-to-video adds another production workflow by generating motion and visual sequences around an existing audio track. The model’s multi-shot generation and synchronized audio can also support storyboarding, concept visualization, previsualization, marketing content, social video, and integration into developer-built creative applications.
LTX describes LTX-2.5 as an open model with open weights that can be executed locally and fine-tuned. The company provides workflows for ComfyUI as well as native Python pipelines for developers.
Yes. LTX-2.5 generates synchronized video and audio and includes dedicated video and audio VAEs in its open model architecture. It also supports audio-to-video workflows in which an existing audio clip conditions the generated video.
Native multi-shot generation allows a single generation to create multiple connected shots while maintaining consistency in elements such as characters, scenes, lighting, visual style, and voice across cuts.
Yes. LTX provides model weights and instructions for running LTX-2.5 locally using ComfyUI or Python-based pipelines. The official documentation currently specifies substantial GPU and system-memory requirements for local use.
LTX-2.5 supports generation conditioned by text, images, video, and audio. Hosted model endpoints include text-to-video, image-to-video, and audio-to-video workflows, while the open model provides additional customization options.
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