Hi everyone. I’m Zeev Farbman, Co-founder & CEO of Lightricks.
I’ve spent the last few years working closely with our team on LTX-2, a production-ready audio–video foundation model. This week, we did a full open-source release of LTX-2, including weights, code, a trainer, benchmarks, LoRAs, and documentation.
Open releases of multimodal models are rare, and when they do happen, they’re often hard to run or hard to reproduce. We built LTX-2 to be something you can actually use: it runs locally on consumer GPUs and powers real products at Lightricks.
I’m here to answer questions about:
Ask me anything!
I’ll answer as many questions as I can, with some help from the LTX-2 team.
Verification:
The volume of questions was beyond all expectations! Closing this down so we have a chance to catch up on the remaining ones.
Thanks everyone for all your great questions and feedback. More to come soon!
https://arstechnica.com/ai/2026/03/google-says-new-turboquant-compression-can-lower-ai-memory-usage-without-sacrificing-quality/
Why has no one created a QR Monster ControlNet for any of the newer models? I feel like this was the best ControlNet. Canny and depth are just not the same.
Thank you Chinese devs for providing for the community if it not for them we'll be still stuck at stable diffusion 1.5
Never forget…
Link: https://huggingface.co/Tongyi-MAI/Z-Image Comfy https://huggingface.co/Comfy-Org/z\_image/tree/main/split\_files/diffusion\_models
https://youtu.be/54IxX6FtKg8 A year ago, I never imagined I’d be able to generate a video like this on my own computer. (5070ti gpu) It’s still rough around the edges, but I wanted to share it anyway. All sound effects, excluding the background music, were generated with MMAudio, and the video was upscaled from 720p to 1080p using SeedVR2.
Workflows from the Neura Market marketplace related to this Stable Diffusion resource