ltx/ltx-v2 models

ltx-v2 by Lightricks — AI Model Family

The ltx-v2 family from Lightricks represents the second generation of their advanced LTX video models, delivering faster, more coherent AI-generated videos with native synchronized audio. Built on a powerful Diffusion Transformer (DiT) architecture with 19 billion parameters, this family solves key challenges in video creation by enabling seamless text-to-video and image-to-video generation in a unified audiovisual framework, producing high-quality outputs up to 4K resolution at 50fps. As an evolution of LTX v1, ltx-v2 emphasizes speed, temporal consistency, and multimodal synchronization, making professional-grade video production accessible for creators, marketers, and developers. The family includes four core models: Ltx v2 | Image to Video | Fast, Ltx v2 | Image to Video, Ltx v2 | Text to Video | Fast, and Ltx v2 | Text to Video, spanning Image to Video and Text to Video categories with fast variants for efficient workflows.

ltx-v2 Capabilities and Use Cases

The ltx-v2 family excels in generating dynamic videos with expressive lip sync, natural motion, and synchronized audio directly from text or images, supporting flexible resolutions where width and height are divisible by 32 and frame counts by 8 plus 1.

• Ltx v2 | Text to Video | Fast and Ltx v2 | Text to Video transform descriptive text prompts into complete videos with audio, ideal for quick storyboarding or social media clips. For example, use the prompt: "A cozy cabin in a snowy forest at dusk, smoke rising from the chimney, gentle wind sounds and crackling fire audio." These models shine in marketing campaigns, generating cinematic sequences with dynamic motion in seconds for the fast version or higher fidelity in the standard one.

• Ltx v2 | Image to Video | Fast and Ltx v2 | Image to Video animate static images into fluid videos, adding realistic movement and sound. Perfect for product demos, upload a photo of a smartphone and generate: "The smartphone rotating on a sleek table with soft ambient music and subtle glow effects." This brings stills to life for e-commerce visuals or concept art extensions.

These models support pipeline creation, such as starting with Text to Video for initial generation, then refining with Image to Video using keyframes from the output for extended sequences. Technical specs include up to 4K at 50fps, native audio-video sync, and compatibility with tools like ComfyUI for workflow integration, enabling distilled fast modes for rapid iteration without quality loss.

What Makes ltx-v2 Stand Out

ltx-v2 sets itself apart with its unified DiT-based architecture that generates synchronized video and audio in one model, ensuring lip sync and temporal coherence unmatched in prior versions—faster and more consistent than v1. Key strengths include native 4K support at 50fps, expressive motion control, and open-source accessibility with full model weights and training code, allowing customization via fine-tuning or LoRAs for specialized effects like pose or depth guidance.

Unlike fragmented tools, ltx-v2 handles multiple modalities seamlessly: detailed prompts yield precise visuals and audio, with features like natural lip sync for talking heads or environmental sounds for immersive scenes. It's ideal for content creators needing quick prototypes, filmmakers requiring cinematic quality, marketers producing ads, and developers building apps with on-device deployment. Market perception highlights its efficiency—fast modes optimize for speed while pro variants deliver ultra-high fidelity—positioning it as a game-changer for scalable video AI.

Access ltx-v2 Models via each::labs API

each::labs is the premier platform for harnessing the full ltx-v2 family through a unified API, giving developers instant access to all four models without complex setups. Experiment in the interactive Playground for prompt testing or integrate via SDK for production apps, supporting seamless text-to-video and image-to-video pipelines with audio sync. Sign up to explore the full ltx-v2 model family on each::labs.