LTX Video 2.3 is one of the best open-source AI video models right now. It generates cinematic footage from text or images — fast, with strong motion quality and native 4K output. But running it locally demands serious GPU power. That's why a lot of creators turn to RunPod.
This guide covers how to run LTX Video 2.3 on RunPod, what you need to get started, and when it makes sense to skip that setup entirely.
What Is LTX Video 2.3?
LTX Video 2.3 is the latest generation model from Lightricks. It's open-source, which means you can download the weights and run it yourself — locally or on a cloud GPU platform like RunPod.
Compared to previous versions, 2.3 delivers significantly less freezing, better motion consistency, and tighter prompt adherence. The community on Reddit described the jump as "less Ken Burns, more real motion" — which is a good summary of what the upgrade feels like in practice.
The catch: the model is heavy. You need at least 16GB of VRAM for basic generations. 24GB is more comfortable for longer clips or higher resolutions.
How to Run LTX Video 2.3 on RunPod
RunPod is a cloud GPU rental service. You spin up a machine with enough VRAM, load your workflow, and generate video without burning out your own hardware.
Here's the basic flow:
- Create a RunPod account and add credits at runpod.io
- Launch a pod — select a GPU with at least 24GB VRAM (RTX 4090 or A100 are common choices)
- Install ComfyUI inside your pod, either manually or via a pre-built template
- Download the LTX Video 2.3 model weights from Hugging Face into your ComfyUI models directory
- Install the LTX Video ComfyUI nodes and load your workflow
- Run your first generation
It works well once it's configured. But "once it's configured" is doing a lot of work in that sentence. Most people spend 30–60 minutes troubleshooting before they get a clean output — node version mismatches, missing dependencies, VRAM errors.
The Faster Route: LTX Video 2.3 in the Browser
If you want LTX Video 2.3 without the RunPod setup overhead, ltx-23.app runs the same model in the browser.
No pod rental. No ComfyUI. No GPU sizing decisions. You write a prompt or upload a reference image, set your aspect ratio and duration, and generate. The whole thing runs on cloud inference — you get the output as an MP4 ready to download.
It uses a credit system with one-time packs (no subscription), and credits don't expire. For creators who generate weekly content or pitch decks, the unit economics come out comparable to RunPod once you factor in the time saved on setup and maintenance.
Which Approach Is Right for You?
RunPod makes sense if you need full control — custom workflows, fine-tuned models, or high-volume batch generation. The setup cost is real but it's a one-time investment.
If you want to try LTX Video 2.3 quickly, prototype ideas, or generate video for client work without managing infrastructure, the browser-based route is faster to start and easier to maintain.
Either way, LTX Video 2.3 is worth the effort. The quality jump over previous open-source video models is real — and it keeps getting better with each release.