r/LTXvideo

▲ 46 r/LTXvideo+1 crossposts

I don't think ComfyUI fully supports LTX 2.5 yet.

Maybe I'm missing something, or the official implementation is in the works, but one of the big hullabaloos of LTX 2.5 is DFR (Diffusion Fidelity Rendering). It's basically the first thing mentioned in the comfyui blog post about it. But...and this is awkward because I love comfy and everybody working on it.. it turns out, the full official DFR pipeline from Lightricks’ own LTX-2 GitHub repository is NOT actually implemented in ComfyUI.

But, wait! what if it's hidden inside the current implementation?...is what i asked chatgpt, when i went down this, couple of days deep rabbit hole. long story short, no it's not.

And therefore, I present to you actual native LTX-2.5 Spatial DFR in ComfyUI!

Here's a quick teaser from what I have working so far.

  • T2V — fox / forest stress test

​

A low-angle wildlife documentary action-chase shot follows a red fox sprinting at full speed through a dense wet pine forest at dawn,backlit from the rising sun behind him, photographed with fully photorealistic natural detail. The camera races beside and slightly ahead of the fox at matching speed, keeping its head and upper body consistently framed while nearby ferns, wet grass and tree trunks sweep past with strong foreground and middle-ground parallax. The fox runs desperately, ears pulled back and body stretched through each stride; its paws kick wet leaves and droplets from the ground while its fur, whiskers and facial detail remain visible during the motion. Behind it, something enormous advances through the far forest but never enters the frame: first a distant tree top suddenly shudders, then a heavy branch snaps and splinters, and a moment later another heavy branch crashing through and falling with a violent impact noticeably closer, sending leaves and broken twigs outward as the unseen pursuer continues gaining ground. The fox briefly glances backward without slowing, then accelerates as the disturbance approaches, while layered morning mist and distant trees remain stable enough to preserve a strong sense of depth. Cold dawn light filters naturally through the canopy and catches moisture on fur, bark and vegetation. realistic anatomical deformations, Rapid paws stretching forward then crashing down on wet earth, the fox's breathing, distant cracking timber and deep approaching impacts dominate the soundscape. No cut, no visible monster, no fantasy styling or exaggerated debris explosion.

Same prompt, dimensions, duration, and Stage 1/Stage 2 seeds. Top: normal Vanilla two-stage. Bottom: native spatial DFR + Pixel Spatial Stage 2. Muted because audio loudness is not parity-controlled. ->> Watch fur, grass, bark, branches, mist, and how the camera/subject trajectories diverge.

  • I2V — cybernetic girl fidelity test against official reference I2V example

​

Use the provided start image as the first frame. The cybernetic figure slowly turns his head to the right, his glowing blue eyes scanning the horizon, mechanical joints in his neck whirring faintly. The camera follows his gaze, panning across the rooftop to reveal the city beyond: a river of light winding between dark towers, a flying vehicle gliding past between the buildings, its lights streaking. He watches it pass, then his eyes narrow slightly. The camera settles on his profile against the city glow, distant hover traffic humming, wind gusting across the rooftop. No text, no black frames.

Same prompt, dimensions, duration, and Stage 1/Stage 2 seeds. Top: normal Vanilla two-stage. Bottom: native spatial DFR + Pixel Spatial Stage 2. Muted because audio loudness is not parity-controlled. ->> Watch facial identity, cybernetic edges, lighting transitions, and background city structure.

So, the obvious question, how much slower is it? Yes, but it only became obvious to me when I started writing this post. Sorry, but when I was trying to get this to work I really didnt care how long it took. I was more focused on vram, memory loads, what was happening with sampling etc. But generally, I don't remember feeling a big difference at all. Anyway, I'm currently running tests with comfy-benchmark so I'll get back to you on this. :)

Oh I kept emphasizing "Spatial" DFR cause theres a Temporal upscaling in the full DFR pipeline. Already working on it, but I felt maybe this was a good enough milestone to share with you. It'll help make your LTX gens so much better.

So I'm finishing the final cleanup in repo and benchmark pass. Full update later today with all results, side-by-side comparisons, generated DFR keyframes, execution-time + VRAM benchmarks, workflows, and public access to the project.

reddit.com
u/gamaraala1 — 2 days ago

LTX 2.5 - Full-resolution workflows (no downscaling-upscaling)

LTX-2.5 is Lightricks' open video generation model and once again they have taken the Comfy UI image-to-video workflow and applied their downscaling-rendering-upscaling technique presumably so it runs faster and works on lower-spec hardware - which is fair enough.

But for those of us who invested in Jensen Huang's next leather jacket by buying a DGX Spark can use the extra memory room for rendering at full resolution.

Here are the workflows, adapted from the original Comfy UI LTX 2.5 templates and working with the same models:

LTX 2.5 Image to Video Full Resolution

https://cdn.lansley.com/comfyui-assets/LTX%202.5%20Image%20to%20Video%20FullRes.json

LTX 2.5 Text to Video Full Resolution

https://cdn.lansley.com/comfyui-assets/LTX-2.5%20Text%20to%20Video%20FullRes.json

These workflows are set to the distilled BF16 version of LTX 2.5 but work just as well with the distilled 'int8-convrot' version in terms of better detail in the full resolution versions compared to the templates supplied by Comfy.

The difference is most noticeable in Image to Video when the you want the action to depart significantly from the supplied first frame. The supplied template struggles to re-apply the detail during the upscaling section of the workflow whereas the full-res version keeps the detail in every frame especially when new content has to be invented that was not in the first frame.

The Text to Video workflow includes a prompt about two guys playing ball on a beach involving the need for detailed sea surf and sand resolution, which was noticeably better in this full resolution version compared to the supplied template workflow using the same prompt ('enhance prompt' tuned off).

The performance of the full resolution versions are of course much slower.

Supplied reduced-res template: 8 x 8 seconds + 3 x 33 seconds = 163 seconds.

That's 8 x low-res rendering steps then 3 x upscale steps.

Full-res text to image is 8 x 33 seconds = 264 seconds (rendering steps only of course).

As ever, trust nothing you ever download and make sure the flowchart JSON files look OK before running them in ComfyUI. Otherwise, enjoy! Would be great to get your feedback.

reddit.com
u/nickinnov — 2 days ago
▲ 17 r/LTXvideo+1 crossposts

LTX 2.5 - Full-resolution workflows (no downscaling-upscaling)

LTX-2.5 is Lightricks' open video generation model and once again they have taken the Comfy UI image-to-video workflow and applied their downscaling-rendering-upscaling technique presumably so it runs faster and works on lower-spec hardware - which is fair enough.

But for those of us who invested in Jensen Huang's next leather jacket by buying a DGX Spark can use the extra memory room for rendering at full resolution.

Here are the workflows, adapted from the original Comfy UI LTX 2.5 templates and working with the same models:

LTX 2.5 Image to Video Full Resolution

https://cdn.lansley.com/comfyui-assets/LTX%202.5%20Image%20to%20Video%20FullRes.json

LTX 2.5 Text to Video Full Resolution

https://cdn.lansley.com/comfyui-assets/LTX-2.5%20Text%20to%20Video%20FullRes.json

These workflows are set to the distilled BF16 version of LTX 2.5 but work just as well with the distilled 'int8-convrot' version in terms of better detail in the full resolution versions compared to the templates supplied by Comfy.

The difference is most noticeable in Image to Video when the you want the action to depart significantly from the supplied first frame. The supplied template struggles to re-apply the detail during the upscaling section of the workflow whereas the full-res version keeps the detail in every frame especially when new content has to be invented that was not in the first frame.

The Text to Video workflow includes a prompt about two guys playing ball on a beach involving the need for detailed sea surf and sand resolution, which was noticeably better in this full resolution version compared to the supplied template workflow using the same prompt ('enhance prompt' tuned off).

The performance of the full resolution versions are of course much slower.

Supplied reduced-res template: 8 x 8 seconds + 3 x 33 seconds = 163 seconds.

That's 8 x low-res rendering steps then 3 x upscale steps.

Full-res text to image is 8 x 33 seconds = 264 seconds (rendering steps only of course).

As ever, trust nothing you ever download and make sure the flowchart JSON files look OK before running them in ComfyUI. Otherwise, enjoy! Would be great to get your feedback.

reddit.com
u/Hefty_Scallion_3086 — 4 days ago
▲ 63 r/LTXvideo+2 crossposts

ComfyUI Tutorial First Test Of LTX 2 5 New Model Better Than Minimax H3

First testing of the LTX 2.5 with a 6GB VRAM I’ve created a low-VRAM workflow that supports both Text-to-Video and Image-to-Video, optimized specifically for GPUs with 6GB of VRAM. The goal is to make LTX 2.5 more accessible to users who don’t have high-end GPUs, while keeping the workflow simple and easy to use. If you’re interested in testing LTX 2.5 on a 6GB GPU, check out the workflow and let me know how it performs on your setup!

Video Resolution : 1344x768 for 7 seconds video
Generated Time : 10 min

The model seems very fast the motions are better, lipsync and sound too, however the quality in minimax is better to me

Workflow link

https://civitai.com/articles/33897/comfyui-tutorial-first-test-of-ltx-2-5-new-model-better-than-minimax-h3

youtu.be
u/cgpixel23 — 6 days ago
▲ 2 r/LTXvideo+1 crossposts

LTX 2.5 on 10GB Vram

I have not posted here before, but I have searched this subreddit and others repeatedly for a clue to answer my question.

Does anyone have a functional workflow for LTX 2.5 video generation using a 3080 with 10 GB VRAM and 32 GB system RAM?

I have also spend more than 2 days with google AI where they sent me down deep and branching rabbit holes only to find that the node suggested did not exist or did not work or the huggingface or civitai file was not available or did not work. Numerous times they sent be back to nodes and arrangements that I hade tried before (and failed) after they suggested it.

A large circle of random guesses by the AI agent. They even admitted it after I called them out on their failure to help.

Any help from others that have been down this pathway would be greatly appreciated.

reddit.com
u/Here4CYDY — 5 days ago
▲ 1.1k r/LTXvideo+2 crossposts

LTX-2.5 is Here

LTX-2.5 went live today. It's a big upgrade to the existing LTX architecture, with nearly every stage of the pipeline reworked, on top of a larger training set and reinforcement-learning post-training. The short version: you can now generate a whole multishot scene in one pass, complex prompts hold together far better, and the output is sharper. 

The Highlights

Full details are available on our blog. Here’s the highlights of this release:

Native multishot. One generation produces multiple connected shots that hold character identity, environment, lighting, voice, and style across cuts.

Diffusion Fidelity Rendering. Instead of locking every scene to one compression rate, the model allocates compute by scene complexity and budget, dynamically allocating more compute to visually demanding moments and less where it is not needed.

Better distilled model. The distilled model keeps far more of the full model's quality at much lower compute, so near-full quality is realistic on GPUs you already have.

And much more.

Where to get everything:

We can't wait to see what you make with it.

u/ltx_model — 9 days ago

Wan2gp "endless tunnel" video 1st attempt WATCH IN 4K

Heres my most recent video with audio.... made with rtx3050 12gb vram 32g system ram. should i continue the journey??? let me know what you think would be cool to add or remove... (i know the lighting gets very dark on a couple parts of it will try to avoid that next go...) figured id go with something easy after the more complicated music videos ive been creating. make sure you watch in 4k .... much better looking on mobile tbh

youtube.com
u/Zealousideal-One2919 — 5 days ago
▲ 2 r/LTXvideo+1 crossposts

Ltx 2.5 open source coming today

LTX 2.5 is releasing today, and from one of the example videos I’ve seen, face distortion still doesn’t seem fully fixed.

That’s already a weak spot for LTX. With MiniMax H3 raising the bar, I’m genuinely wondering how LTX 2.5 plans to compete. 👀

I think LTX 2.5 already lost here 🤣🤣🤣

u/EverythingMacPro — 9 days ago
▲ 5 r/LTXvideo+1 crossposts

New Trainer Drop :)

My new video/image LoRA trainer has just been released. This is a from-scratch rebuild rather than an iteration on our earlier trainers I've shared, and I use it daily.

Current support:

- MiniMax H3, including reference image IC-LoRA training (additional reference

modalities in progress)

- LTX 2.3 with the fuller IC-LoRA feature set

- LTX 2.5 being implemented now

- Wan 2.1 and Qwen / Qwen-Image-Edit on beta branches, finalizing for merge

We scope model support to what we use in our own exploratory work rather than trying to cover the field. The tradeoff is fewer models, but every one on that list has real LoRAs trained through it with real recipes.

Credit where it's due: musubi-tuner and ostris/ai-toolkit shaped a lot of how we think about trainer architecture, and Lightricks' own LTX trainer is genuinely good reference for the audio-video side.

Happy to answer config questions.

Check it out here

Edit: just flagging, I work professionally in applied ai and built this for the platforms and GPUs I use. Happy to set up other scripts if you open an issue on the GitHub for additional support, and also agents should have no problem converting it.

u/Sea-Bee4158 — 8 days ago
▲ 20 r/LTXvideo+3 crossposts

Opinions on Full Lip Sync Music Video

This is the 2nd full lip sync music video I've made. It was rendered entirely locally using LTX-2.3 with original audio imported in. I generated it in 1080P but I used CapCut to upscale to 4k and drop the audio back in so it was cleaner. I'm looking for some honest opinions/criticism/feedback before I make the video public on Friday.

The theme I was going for is Mythraelis begins alone in a dim blue-lit apartment at night, emotionally distant and searching. She is pulled through soft digital thresholds. Each transition reveals a deeper layer of the feed.

youtu.be
u/Affectionate_Oil28 — 13 days ago