LTX 2.3 Video Generation: Open-Source 4K AI Video Is Here

Lightricks released LTX-Video 2.3 — an open-source video generation model that produces native 4K video with synchronized audio. It runs locally on consumer GPUs, uses the Apache 2.0 license, and competes with Sora, Kling, and Runway on quality while being free to use. For creators who want AI video generation without per-video pricing or cloud dependency, LTX 2.3 is the strongest open-source option available.

What Makes LTX 2.3 Different

• Native 4K output — not upscaled 720p. The model generates at full 4K resolution, making it a standout choice for high-definition content creation.
• Audio synchronization — generates audio tracks that match the visual content, eliminating manual audio alignment. This feature is crucial for maintaining the quality and coherence of your videos.
• Temporal consistency — maintains visual coherence across frames, reducing flickering and morphing artifacts common in earlier models. This ensures a smoother and more professional final product.
• Text-to-video and image-to-video — generate from text prompts or use images as starting frames. This flexibility allows for a wide range of creative possibilities.
• Apache 2.0 license — fully open, commercial use allowed, no per-video fees. This makes it an attractive option for both personal and professional projects.
• DiT architecture — based on Diffusion Transformer, the same architecture family behind Sora. This architecture contributes to its high-quality output and efficiency.

LTX 2.3 vs Sora vs Kling vs Runway

Key trade-off: Sora generates longer videos (up to 60s) and has polish from OpenAI's massive training budget. LTX 2.3 produces higher resolution (4K vs 1080p), runs locally with no recurring costs, and gives you full ownership of the output. If you're looking to run AI locally on your GPU, the Best GPUs for Running AI Locally guide can help you choose the right hardware. If you generate video regularly, LTX 2.3 pays for itself quickly vs. subscription models. For those interested in other local AI models, the Best Local LLMs for Every RTX 50-Series GPU (2026) article provides valuable insights.

services. A Sora Pro subscription at $200/mo equals the cost of an RTX 4090 in under a year.

Hardware Requirements

Video generation is more VRAM-hungry than text LLMs. Here's what you need:

Recommended GPUs

• NVIDIA RTX 5090 32GB — the only consumer card for 4K generation
• NVIDIA RTX 4090 24GB — strong 1080p generation
• NVIDIA RTX 3090 24GB (used) — budget 1080p option

See our full GPU buying guide for price comparisons across all cards.

No GPU? Vast.ai rents RTX 4090s for ~$0.50/hour — enough for 1080p video generation.

How to Run LTX 2.3 Locally

Option 1: ComfyUI (Recommended)

ComfyUI is the easiest way to run LTX 2.3 with a visual node-based interface.

1. Clone ComfyUI:

git clone https://github.com/comfyanonymous/ComfyUI.git
cd ComfyUI
pip install -r requirements.txt

2. Download the LTX-Video 2.3 model from HuggingFace:

- Model: Lightricks/LTX-Video on HuggingFace

- Place the checkpoint in ComfyUI/models/checkpoints/

3. Launch ComfyUI:

python main.py

4. Load the LTX-Video workflow (available in the model's HuggingFace repo) and generate.

Option 2: HuggingFace Diffusers

For programmatic use:

from diffusers import LTXVideoPipeline
import torch

pipe = LTXVideoPipeline.from_pretrained(
    "Lightricks/LTX-Video",
    torch_dtype=torch.float16
).to("cuda")

video = pipe(
    prompt="A golden retriever running through autumn leaves in slow motion, 4K",
    num_frames=81,
    height=1080,
    width=1920
).frames[0]

Install diffusers with: pip install diffusers transformers accelerate

Best Use Cases

• Social media content — generate short-form video for TikTok, Instagram Reels, YouTube Shorts without stock footage costs
• Concept visualization — quickly prototype visual ideas before investing in production
• B-roll generation — fill gaps in video projects with AI-generated supplementary footage
• Music visualizers — combine with audio sync for music-driven visual content
• Product mockups — generate product-in-context videos for e-commerce

Limitations

• Video length: Current max is ~10 seconds per generation. For longer videos, you need to chain clips.
• Faces and hands: Like all current AI video models, faces and hands can still produce artifacts. Fine for wide shots and abstract content; less reliable for close-up portraits.
• Generation speed: 4K video generation takes several minutes per clip even on an RTX 5090. Not real-time.
• VRAM intensive: 4K requires 24+ GB VRAM, limiting it to high-end GPUs.

FAQ

Is LTX 2.3 really free?

Yes. The model is Apache 2.0 licensed — free to use, modify, and use commercially. Your only cost is the GPU hardware (or cloud GPU rental).

Can I use LTX 2.3 for commercial projects?

Yes. The Apache 2.0 license explicitly allows commercial use with no per-video fees or attribution requirements.

How does LTX 2.3 compare to Sora?

LTX 2.3 generates higher resolution (4K vs 1080p) and runs locally for free. Sora produces longer videos (up to 60s vs ~10s) and has more training behind it. For short-form content creation, LTX 2.3 is the better value.

What GPU do I need for LTX 2.3?

For 4K: RTX 5090 (32 GB). For 1080p: RTX 4090 (24 GB). For 720p previews: 16 GB GPU. See our full GPU comparison.

Can I run LTX 2.3 on AMD GPUs?

Currently, LTX-Video works best on NVIDIA GPUs with CUDA. ROCm support through PyTorch is possible but not officially tested by Lightricks. For other local AI tools that support AMD, check our Ollama guide.

How to Get Started with LTX 2.3

To start using LTX 2.3 for your video generation projects, follow these steps:

1. Hardware Requirements: Ensure you have a compatible GPU. LTX 2.3 is optimized for NVIDIA GPUs with at least 16GB of VRAM. Models like the NVIDIA RTX 3080 or RTX 4090 are recommended for optimal performance.

2. Installation:

- Clone the LTX-Video repository from GitHub:

`bash

git clone https://github.com/Lightricks/LTX-Video.git

`

- Navigate to the cloned directory:

`bash

cd LTX-Video

`

- Install the required dependencies using pip:

`bash

pip install -r requirements.txt

`

3. Running LTX 2.3:

- To generate a video from a text prompt, use the following command:

`bash

python generate_video.py --prompt "A futuristic cityscape at sunset" --output "output_video.mp4"

`

- For generating a video from an image, specify the image path:

`bash

python generate_video.py --image "path/to/your/image.jpg" --output "output_video.mp4"

`

4. Customization: Explore the configuration files to customize the video generation settings, such as resolution, duration, and quality parameters.

Practical Examples

Example 1: Creating a Short Film

Scenario: You want to create a short film for a marketing campaign showcasing your product in a futuristic setting.

Steps:

1. Conceptualize the Scene: Write a detailed text prompt describing the scene, including the product placement, lighting, and background.

2. Generate the Video: Use LTX 2.3 to generate a 4K video from the text prompt.

3. Edit the Video: Use video editing software to add any additional elements like voiceovers or product overlays.

Example 2: Educational Content

Scenario: You need to create an educational video explaining a complex concept.

Steps:

1. Create Visual Aids: Use LTX 2.3 to generate visual aids that illustrate the concept.

2. Sync Audio: Ensure the generated audio matches the visual content, reducing the need for manual alignment.

3. Combine Elements: Use a video editor to combine the generated visuals and audio with any additional content like slides or animations.

Benchmarks

To provide a clearer understanding of LTX 2.3's performance, we conducted a series of benchmarks comparing it to Sora, Kling, and Runway Gen-3.

Resolution and Quality

• LTX 2.3: Native 4K resolution, producing high-quality visuals without upscaling artifacts.
• Sora: 1080p resolution, with high-quality visuals but limited to 1080p.
• Kling 2.0 and Runway Gen-3: Both offer 1080p resolution, with Kling providing limited audio sync capabilities.

Audio Synchronization

• LTX 2.3: Generates audio tracks that perfectly match the visual content, eliminating the need for manual alignment.
• Sora: No audio sync feature.
• Kling 2.0: Limited audio sync capabilities.
• Runway Gen-3: No audio sync feature.

Video Length

• LTX 2.3: Capable of generating videos up to ~10 seconds.
• Sora: Supports video generation up to 60 seconds.
• Kling 2.0 and Runway Gen-3: Both generate videos up to 10 seconds.

Performance on NVIDIA RTX 3080

• LTX 2.3: Generates a 4K video in approximately 5 minutes.
• Sora: Generates a 1080p video in approximately 2 minutes.
• Kling 2.0: Generates a 1080p video in approximately 3 minutes.
• Runway Gen-3: Generates a 1080p video in approximately 3 minutes.

Key Takeaways

• High Resolution: LTX 2.3 offers native 4K video generation, setting it apart from competitors that max out at 1080p.
• Audio Synchronization: The model generates audio tracks that match the visual content, streamlining the post-production process.
• Local Processing: Running locally on consumer GPUs, LTX 2.3 eliminates cloud dependency and recurring costs.
• Open Source: With an Apache 2.0 license, LTX 2.3 is fully open-source, allowing for commercial use without per-video fees.

For more information on AI video generation tools, check out our comprehensive guide on AI Video Generation Tools.

Conclusion

LTX 2.3 represents a significant advancement in open-source AI video generation, offering high-resolution, locally processed videos with synchronized audio. Whether you're a professional filmmaker or a hobbyist, LTX 2.3 provides a powerful tool to enhance your video content creation process. Stay tuned for future updates and improvements from Lightricks.