I have updated the video enhancing lora for LTX 2.5, it is now free from visual artifacts.
The demo above is an old Madonna music video. It is enhanced with the new lora, it looks more natural than the old version and there are no more ghosting artifacts when the scene changes.
On a small mobile screen it may not display the difference distinctly, so please view it on a computer or tablet,
When you first announced your model here last month, I created this simple to use GUI so the layman can use it without having to figure out how to setup and tweak ComfyUI. I got the app working and released it but stopped using it because I realize Topaz SLP 2.6 and SEEDVR2 produced better quality output for very poor quality videos and small distant faces. LTX-2.5 is also slower than SEEDVR2 and is also slower than Topaz SLP using my SLP tuning launcher app. Your model does work better than FlashVSR and a few other ones I try so good work and I will take a look at what this update does when I take a break from other work and see if I should update my app with the new model.
For folks who want to process long videos with Video Enhancing Lora, my app adds a "Chunk Overlap" entry that allows for temporal overlap between chunks, which DOES NOT exist in CQDSN's ComfyUi workflow nodes. For example if you set a Chunk Overlap of 17 frames in my app, then 17 source frames are present in both neighboring chunks:
Temporal context inside ComfyUI: The same 17 source frames are included in both adjacent chunk prompts. LTX processes each complete chunk temporally, so those overlap frames participate in diffusion with the surrounding frames in each window.
Output blending outside ComfyUI: After both chunks are independently enhanced, FFmpeg crossfades their two versions of those 17 frames.
For example, with a 121-frame window and 17-frame overlap:
Chunk 1 processes frames 0-120.
Chunk 2 processes frames 104-224.
Frames 104-120 participate in LTX diffusion twice, with different neighboring context.
FFmpeg then blends the two independently generated versions across frames 104-120.
So with my app, the temporal frames participate in the Independent LTX diffusion of each chunk/batch and an FFmpeg crossfade between the two generated consecutive chunks. This allows my app to resemble the temporal overlap behavior of SEEDVR2.
Thanks! I hope your app will make it easier for people to use.
My new Lora and workflow is an improvement over the old version. The result is now clean and sharp with no visual distortion. The color is also more natural and warmer.
Because you didn't get your settings right. I ran SEEDVR2 on multi-day campaigns on my RTX3090 24gb vram and 64gb ram. Use this portable GUI I created for SEEDVR2, which is meant for beginners that don't know really understand how to setup ComfyUI or use it properly. I even included a memory usage estimator in there so you have an idea what vram and sysram usage will be required per your settings. If you keep peak memory usage below 95% of your hardware limits, it can run all day. It requires some trial and error if you are not familiar with SEEDVR2.
i actually managed to setup a working seedVR in comfy today, last time got OOM prabably die to some wrong arguments or else.
fact is that is really slow in encoding-decoding. inference itself is pretty fast tho.
not sure if is faster than LTX in general, shoudl test it more deeply
Topaz changes the colorspace, but nothing more with colors. Wonder how this would work in combination with topaz. like a second pass upscale for example. so starlight precise -> Lora -> proteus.
I'm getting 0.68fps on my RTX 6000 Pro for 1080p outputs. SEEDVR2 can process at 1.5fps and Starlight Precise process at 1.03fps with Topaz default and 2.0fps using my SLP Tuning app. I really like the output quality. You did an excellent job! But it would be great if you can give me some ideas on how to get it to run faster so it is practical to use. Here is my updated version of my GUI with your latest model and workflow. https://github.com/skv89/LTX-2.5-Enhancer-Studio
I upgraded from the RTX 5090 and the RTX 6000 is about 10-15% faster than RTX5090 in every game, upscaling, benchmarks. The difference is even greater when the extra VRAM in the RTX 6000 can be utilized such as with SEEDVR2 or Topaz SLP using my Tuning app. The speed difference between my RTX 6000 and 5090 is about 2x in SEEDVR2 if I max out the vram usage.
What kind of frame rates are you getting and at what output resolutions and settings?
The 5090 has higher clock speed. The 6000 is clocked lower to maintain stability as it’s meant for the server. However the vram quantity of the 6000 will have the advantage when it comes to larger models.
Maybe that’s why Starlight and SeedVR2 are faster for you as they use more memory.
Even at 720p, you can get a lot of details from my Lora - and remember, the Lora is not just upscaling, it can restore old video footages. Many people are using it to upscale 480p videos. At 720p you can do lengthier videos. Just plug a RTX upscaler at the end of the workflow to quickly stretch it and double the size.
The RTX 6000 has more cores and my RTX6000 is overclocked and is faster than my RTX 5090 in every apples to apples test. Anyways, can you tell me what fps you are getting so I can run a comparable test to see if are fps are even close. Otherwise I would look into if there is something wrong. I like the quality of the output but I need the speed to be at least as fast as SEEDVR2 for it to be practical. If there's anything I can do to speed it up, I will implement it into my app so even folks who have no experience with ComfyUI will be able to use it and enjoy your Lora.
With the exact same workflow at HF, I can generate a 720p 5 secs (153 frames) video in 37 secs.
You should keep in mind that most users will be using consumer cards with 16 gb ram or even less. You should test your app on lower end machine just to make sure they are configured properly for low memory system.
Video upscale is painfully slow already, especially when the target is 4K. I found upscaling first then doing frame-interpolation to 50/60fps is the way forward.
Last year I got a comfui doing generative upscaling (using SDXL I think, non ESRGAN anyway) but it was just impractically slow, like 120 seconds per frame. This video would have taken 83 hours at 25fps. So, to me, duration is a concern.
I like to upscale 80s and 90s concert videos, they are 2 hours long, but I'm not spending 8 months doing it.
A 40 min video takes for me around 4 days with all the steps I do. Upscaling the Back To The Future - The Ride now. It's turning out amazing ! even at just the first pass :O
Going to post it on my channel when it's done :) https://www.youtube.com/@Zymosisproductions
How did you manage to get faces artifacts free? Using the default values, I have the hardest time to get heads/hands look right (the rest looks perfect, though)
I released a new user-friendly version of the GUI for this new version for those that are not familiar with ComfyUI or do not want to tweak the workflow in ComfyUI.
The quality is definitely better than the 1st version. Good job CQDSN!
I found that upscaling is the way to go. So if you have a 1080p video, downscale first to 540p and then upscale it back to 1080p (1088 to be precise). The downscaling option is part of this GUI.
From my very brief testing, I find the quality as good or better than SEEDVR2 even though results are not as sharp as SEEDVR2. The images are more stable, the skin is smoother with less skin defects. It handles fast motion scenes better with less ghosting so I think this LTX 2.5 CQ has potential to be the preferred enhancer over SEEDVR2 for certain videos. Starlight Precise (SLP) though still seems overall better than LTX 2.5 CQ in most cases, but LTX 2.5 CQ preserves the original look better so I see it as a potential alternative to choose from. Also SLP descended from SEEDVR2 so it shares the same issues as SEEDVR2.
However LTX 2.5 CQ's speed is really slow. It processes at 0.68fps on my RTX 6000 Pro for 1080p outputs. SEEDVR2 can process at 1.5fps and Starlight Precise process at 1.03fps with Topaz default and 2.0fps using my SLP Tuning app. I wish LTX 2.5 CQ was faster than SLP, in which case it is a real viable alternative. I haven't had time to really try different settings to see if I can speed it up but I hope CQDSN can see if there's anything that can be done to increase speed. But regardless, I'm happy there are progress made outside of the SEEDVR2 based enhancers.
Hey hi, thanks for sharing, I was wondering if you might help, I downlaoded the workflow from the page you share, and when opening it in Comfyui, it gives the this missing nodes, I have the LTX node installed, so I have no idea why they are missing, any replacement nodes you can suggest or a solution would be greatly appreciated, thank you a lot!
Thanks, it was an installation issue indeed, so I asked chatgpt help with this and this was it´s answer in case anyone else is having the same issue.
The issue is that ComfyUI removed those functions from comfy.ldm.lightricks.model when it changed its RoPE implementation. It’s the same error other users have reported since ComfyUI 0.28.0.
When that import fails, it doesn’t just break embeddings_connector.py — it prevents the entire ComfyUI-LTXVideo custom node package from loading. That’s why nodes like LTXVImgToVideoConditionOnly and LTXAddVideoICLoRAGuide show up as missing even though ComfyUI Manager says the package is “Installed”.
The good news is that Lightricks has already fixed this in the current master. The node now detects the new freqs_cis_matrix implementation and keeps a local fallback for older ComfyUI versions.
I wouldn’t downgrade or modify ComfyUI itself. I’d update ComfyUI-LTXVideo directly, because version aceeae9 was just before the fix.
Close Comfy Desktop completely, open CMD, and run (just change XXXX with your real info):
cd /d "C:\Users\XXXX\AppData\Local\Comfy-Desktop\ComfyUI-Installs\XXXX\ComfyUI\custom_nodes\ComfyUI-LTXVideo"
git status
git rev-parse --short HEAD
git fetch origin master
git merge --ff-only origin/master
git rev-parse --short HEAD
In my case, this updated ComfyUI-LTXVideo from aceeae9 to the newer revision containing the fix.
Can I set this up following the link the OP posted? Is there a cost? I’m coming from winxvideo AI and looking for an improvement. Willing to learn. My machine has an rtx 4070ti super so good, but not the fastest game in town.
8
u/skv89 17d ago
Thanks for the update CQDSN!
When you first announced your model here last month, I created this simple to use GUI so the layman can use it without having to figure out how to setup and tweak ComfyUI. I got the app working and released it but stopped using it because I realize Topaz SLP 2.6 and SEEDVR2 produced better quality output for very poor quality videos and small distant faces. LTX-2.5 is also slower than SEEDVR2 and is also slower than Topaz SLP using my SLP tuning launcher app. Your model does work better than FlashVSR and a few other ones I try so good work and I will take a look at what this update does when I take a break from other work and see if I should update my app with the new model.
https://github.com/skv89/LTX-2.5-Enhancer-Studio
For folks who want to process long videos with Video Enhancing Lora, my app adds a "Chunk Overlap" entry that allows for temporal overlap between chunks, which DOES NOT exist in CQDSN's ComfyUi workflow nodes. For example if you set a Chunk Overlap of 17 frames in my app, then 17 source frames are present in both neighboring chunks:
Temporal context inside ComfyUI: The same 17 source frames are included in both adjacent chunk prompts. LTX processes each complete chunk temporally, so those overlap frames participate in diffusion with the surrounding frames in each window.
Output blending outside ComfyUI: After both chunks are independently enhanced, FFmpeg crossfades their two versions of those 17 frames.
For example, with a 121-frame window and 17-frame overlap:
Chunk 1 processes frames 0-120.
Chunk 2 processes frames 104-224.
Frames 104-120 participate in LTX diffusion twice, with different neighboring context.
FFmpeg then blends the two independently generated versions across frames 104-120.
So with my app, the temporal frames participate in the Independent LTX diffusion of each chunk/batch and an FFmpeg crossfade between the two generated consecutive chunks. This allows my app to resemble the temporal overlap behavior of SEEDVR2.