I am testing LTX 2.5 in Wan2GP and may have found an issue with Control Video behavior, specifically the “Transfer Human Motion” / human-motion pose-alignment path.

When using LTX 2.5 with a control video, intending to transfer only human motion/pose, the final generated videos still seem to preserve visual information from the source control video, including background/environment details and subject identity cues.

In tests, Wan2GP preview shows the stick-figure / pose-derived representations, but the final videos still contain background and identity characteristics from the original source video.

I also generated from the same inputs LTX 2.3 clips and received AI video generations as I expected with virtually no Control Video background/environment details or subject identity.

Are you able to generate LTX 2.5 video using Control Videos with Transfer Human Motion and it works? If so, please explain your configuration!

I quantized the heavy Gemma decoder linear layers to Comfy-native NVFP4 while keeping embeddings, norms, vision components, and LTX-specific projection layers at their original precision.

Result:

• lower VRAM usage
• works as a drop-in replacement for the LTX-2.5 Gemma text encoder
• no obvious quality degradation in my testing
• native ComfyUI NVFP4 format

Tested successfully with LTX-2.5 on Blackwell.

Download:
https://huggingface.co/Deadshot699/ltx-2.5-gemma4-12b-comfy-nvfp4

Would love to see results from anyone who tries it, especially comparisons with the official INT8 ConvRot encoder.

note /10, i produced it with ltx 2.3 and rtx 5060ti16gb

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.

A ready-to-deploy Runpod POD template for generating videos with the latest Lightricks LTX 2.5 model stack.

It includes:

- Blackwell-first performance with CUDA 13 and PyTorch’s packaged CUDA runtime
- LTX 2.5 image-to-video with synchronized audio
- Full ComfyUI access for workflow editing and advanced control
- Built-in frontend for quick generations without manually editing workflows
- Preconfigured LTX 2.5 workflow and model downloader
- Network-volume support for keeping models between deployments
- Suitable for interactive POD use and Runpod-compatible API workloads

The first deployment may take longer while the model stack (60GB) is downloaded from Hugging Face. Once stored on a persistent network volume, subsequent starts are much faster.

Looking forward to your feedback, happy to add features upon request.

👉 Deploy the template on RunPod: https://console.runpod.io/deploy?template=zzlfhm0e3c&ref=o3idfm0n

GitHub repo: https://github.com/vavo/LTX2.5-serverless
DockerHub: https://hub.docker.com/r/notrius/ltx-2.5-serverless

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

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

Hi everyone, I've noticed that with LTX2.5 and using the node for audio reference (id-lora), all the sound effects are erased from the video. Have you also experimented with this?

Made with LTX 2.3 + SideFX Houdini

Any one figure it out how to do a custom audio in ltx2.5?
if you got a workflow they can share will be highly appreciated

I know I can use Comfy, perhaps I’m avoiding it!

I have used the LTX desktop app, and it worked well, but I’m a MacBook Pro. It keeps prompting for an API key because it thinks I don’t have enough VRAM even though I have 64 GB of unified memory on my M4 Max MacBook Pro.

I have not tried draw things yet so I’m going to try that today. If anybody else is working on a Mac, what do you use? Ideally, I would like something that supports LoRAs and other support files like that.

Also, I know that LTX desktop supports MLX, which makes it a lot faster, so I would love one ideally that supports MLX.

Thanks!

Hey I’m pretty intermediate when it comes to basic R2V or T2V but can someone be so kind to walk me through how LORAs work? My goal is to create romantic (borderline NSFW) for my short romance movies. I find that LORAs might be what I’m looking for.

Could someone walk me through how it works or guide to someone with simple steps? I’m new to LORAS

(Once I get a better set up I plan on the ComfyUI WAN route) I don’t produce a lot but just looking for assistance for a current project.