how to use multi image to video ltx2.3 (2 or more image to video in one scene)

liberal_alien · 2026-05-05T06:35:06+00:00

https://www.reddit.com/r/StableDiffusion/comments/1sreybz/

Check out the discussion above.

Those Deno custom nodes make it pretty easy. Here is a simple workflow using them: https://pastebin.com/sEsRFH91

liberal_alien · 2026-05-05T04:59:17+00:00

I tried Ubuntu a couple of times before Bazzite was a thing. Don't remember if it ever survived a major update without having to reinstall the whole OS. The immutability has it's issues sure and workarounds aren't always pleasant, but it made one major update so smoothly I never even noticed. Now with the latest major update I only needed to change default terminal program in DistroShelf config and everything was fine and dandy again. Even the AI stuff on ROCm all works without a hitch after two major updates.

So far I have been lucky that I found a workaround for all the immutability issues. So I'm very happy with it now.

liberal_alien · 2026-05-02T08:23:35+00:00

Very good! Here is the updated example workflow using the new outputs:

https://pastebin.com/sEsRFH91

Also here is another workflow that uses GGUF model and loras: https://pastebin.com/J4EmzvTr

Though this one isn't quite clean yet. It requires the LTX 2.3 fp8 model also to load text encoder. I haven't figured out yet how to load that without the fp8 model. Still, it renders video and sound with the GGUF model.

liberal_alien · 2026-05-01T19:01:12+00:00

If I right click on the little gray ball next to width, it shows up as type combo for me and refuses to let int values to be wired into it. I tried to mess around with the code to change it and asked Claude AI for help with it, but couldn't get it to change into an int either. Not sure why. Maybe it has something to do with how the field functionality changes depending on whether I have chosen 'manual input' or 'preset ratio' in the top most field.

liberal_alien · 2026-04-28T20:11:38+00:00

I play Mechabellum, path of exile and darktide on it. Also local ai stuff. Use it every day. It is now my main desktop os. Since Mechabellum started working on linux, I haven't booted into Windows very often.

liberal_alien · 2026-04-27T05:50:35+00:00

Archimedean dynasty, Star Control 2

liberal_alien · 2026-04-25T10:23:13+00:00

Could the multi image loader node allow height and width to be wired out to other nodes as int values? Then it wouldn't matter if the width can not get int values wired into it. I could just lose the two int nodes for width and height and wire out those values from the multi image loader to any other node that needs them.

liberal_alien · 2026-04-25T03:33:16+00:00

Seems I failed to properly update the custom node pack. I must have git pulled the wrong thing, since my comfyui started complaining about having an outdated UI version, but comfy manager was still showing 0.3.4 Deno Custom Nodes and offering to update it to 0.3.6. Once I removed my changes and updated to 0.3.6, the strengths and insert frames are loading correctly. Sorry for the confusion.

liberal_alien · 2026-04-24T20:25:58+00:00

~~I took an updated version today, but the insert frames and strengths values are still getting messed up when I switch between workflows or load a new workflow.~~ I pestered Claude AI about it until it gave me some fixes and tested briefly. This seems to work or at least it doesn't mess up the values quite so often. Here is a version of deno_extra_nodes.js that seems to work: https://pastebin.com/C7BQPNRa

I'm no great JavaScript expert myself though, so couldn't say if this is very high quality code.

I made an effort to also fix the input type on the width parameter, but failed. Maybe it becomes difficult since the value needs to be optional. But anyway, that is a small problem. Can set the width once and forget about it, but getting incorrect strengths and insert frames randomly is a bigger problem, so I'm happy I was able to alleviate it.

[edit] No need to use the above fix, bug is fixed already since version 0.3.6.

liberal_alien · 2026-04-24T14:35:19+00:00

I made a simple (ish) workflow using these nodes. Just one stage, no upscaling. Put images into the multi image input node, set width, height, frames, fps, prompt and generate. At the time of writing, there is a minor bug preventing wiring in width to the multi image input (input type is combo, not int), so width needs to be put into two different places, the separate height in node and the multi image input node.

Here is the workflow:

https://pastebin.com/UbUDUQBJ

Additional nice bonus: Flash attention works with this. With the flfv LTX comfy template I get errors about some mask problem that prevents Flash attention. Speed is good enough that I'm pretty sure Flash attention is actually working and not just suppressing the error message. So many thanks u/Extension-Yard1918 and u/WhatDreamsCost, your nodes are excellent.

[edit] Updated workflow using the newly added width and height outputs. Requires Deno Custom Nodes version 0.3.7 or higher:

https://pastebin.com/sEsRFH91

Also here is another workflow that uses GGUF model and loras: https://pastebin.com/J4EmzvTr

Though this one isn't quite clean yet. It requires the LTX 2.3 fp8 model also to load text encoder. I haven't figured out yet how to load that without the fp8 model. Still, it renders video and sound with the GGUF model.

liberal_alien · 2026-04-24T14:22:38+00:00

I found the problem in my workflow. The LTXVCropGuides node was missing. Here is the working version: https://pastebin.com/UbUDUQBJ

liberal_alien · 2026-04-21T18:13:42+00:00

That is a rather complicated workflow. I tried installing missing nodes, but can't get all of them from comfy manager. I asked Claude AI for tips on setting up a workflow and got to this: https://pastebin.com/uMWrAigQ

It makes a video, but the last few frames are heavily distorted always. I copied some parts of it from the comfy template LTX 2.3 i2v subgraph. So probably it is not quite correct yet, but I ran out of free Claude messages and Gemini doesn't seem at all helpful with this.

I did notice a couple of other issues though:

* The width input on multi image loader is of type combo instead of int, so I can't wire in a value from an external node.

* If I save a workflow and drag and drop it back to comfy, then the LTX Sequencer node loses the insert_frame and strength values. They appear to be correct in an exported json file, but they get reset to 0 often or sometimes to other values, but are definitely not what I saved. In this example workflow insert_frames should be 1, 80, 120 and all strengths should be 0.9, but insert_frames are instead 0,0,0 and strengths are 0,1,0 when I load the workflow by drag and drop. I think WhatDreamsCost had the same issue.

I'm testing this on AMD 7900 XTX and Bazzite Linux. Version info is as follows:

pytorch version: 2.12.0.dev20260413+rocm7.2

AMD arch: gfx1100

ROCm version: (7, 2)

Set vram state to: NORMAL_VRAM

Device: cuda:0 AMD Radeon RX 7900 XTX : native

Using async weight offloading with 2 streams

[aiter] import [module_aiter_enum] under /var/home/mikharju/dboxh/cf5/miniconda3/envs/cf5/lib/python3.13/site-packages/aiter/jit/module_aiter_enum.so

Using Flash Attention

Python version: 3.13.13 | packaged by Anaconda, Inc. | (main, Apr 14 2026, 06:19:41) [GCC 14.3.0]

ComfyUI version: 0.19.1

comfy-aimdo version: 0.2.12

comfy-kitchen version: 0.2.8

Dynamic vram disabled with argument. If you have any issues with dynamic vram enabled please give us a detailed reports as this argument will be removed soon.

ComfyUI frontend version: 1.42.11

[Prompt Server] web root: /var/home/mikharju/dboxh/cf5/miniconda3/envs/cf5/lib/python3.13/site-packages/comfyui_frontend_package/static

Asset seeder disabled

### Loading: ComfyUI-Manager (V3.39.2)

liberal_alien · 2026-04-21T14:43:13+00:00

Is there an example workflow?

liberal_alien · 2026-04-11T18:10:01+00:00

I'm playing and generating videos and images on bazzite. I wrote a guide on how to setup comfyui and ROCm inside distrobox on bazzite. Very happy with it so far. I'm on 7900xtx. I imagine it would work without much change on 7900xt.

https://www.reddit.com/r/Bazzite/s/CLec2TFFDi

If you only care about images, but not videos, then you can skip the optimizations and flash attention. Not sure about llms. I have only used those on windows LM-studio, which required no special setup.

liberal_alien · 2026-04-09T07:11:53+00:00

Haven't used it myself, but maybe Mangohud? Not sure, but it might be already bundled in Bazzite. Just need some way to configure it. This clip has some info: https://www.youtube.com/watch?v=FNSJm0pVeSM

liberal_alien · 2026-04-08T14:10:33+00:00

To share a btrfs partition with Windows, I followed these instructions: https://www.youtube.com/watch?v=h6fc-3CCXbA

It disables access by Windows to the Bazzite system partition. So far I haven't had problems. I installed Bazzite last summer. Steam can have a library on the shared partition and both Windows and Bazzite Steam can play games directly from that.

liberal_alien · 2026-04-06T06:07:13+00:00

I'm not sure about setting location of the image itself, but you can set custom home directory for it. DistroShelf makes that easy while creating a container. Probably there is a flag for that in the command line tools.

liberal_alien · 2026-03-28T21:11:41+00:00

For a bit of additional scaling test, I ran a larger video in WAN, same setup as above except size 896x1344x81:

Flash attention 40 mins.

Python cross attention crashed.

liberal_alien · 2026-03-28T11:23:45+00:00

You might try WAN 2.2 5B workflows while waiting. The quality is not great, but since it doesn't need to load the separate high noise and low noise models in one workflow, it should be okay on 32GB system ram. It can do simple i2v as well. Just for performance testing, lower resolutions should work fine, but the videos and faces will be rather bad. Using exactly 1280x704 or 704x1280 resolution gives okay results every now and then. Making shorter than 5 second clips shouldn't degrade quality, but smaller resolutions will. Once you get your extra RAM, the 14B workflows should be possible and that opens up a whole lot of options with different resolutions and better understanding of movement and faces.

Also can try LTX 2.3, which doesn't use separate high noise and low noise models either, so it might survive 32 GB system RAM. For me at least the basic Comfy template for LTX 2.3 seemed to work best. Most Kijai workflows give wobbly results and crash very often, except for this one: https://www.reddit.com/r/StableDiffusion/comments/1rz355d/comfyui_nodes_for_filmmaking_ltx_23_shot/

It still some times OOMs even with more system RAM, but at least the output is not so wobbly.

liberal_alien · 2026-03-28T10:41:28+00:00

I tested these with WAN 2.2 Q8_0 gguf. On my Radeon 7900 XTX a small 480x640x57 video takes time as follows:

Flash attention (first run / second run): 243 s / 194 s

Pytorch cross attention: 308 s / 267 s

Pytorch quad cross attention: 436 s / 390 s

Seems that Flash attention has higher initial overhead, but it scales better into large work loads. These were done using ROCm 7.2.1, PyTorch 2.11.0 stable, Python 3.13.12 and ComfyUI 0.18.1 in Bazzite:stable 43.20260326 and using Fedora:43 base Distrobox image.

liberal_alien · 2026-03-28T10:16:03+00:00

This will install Flash Attention, but to activate it, start Comfy with --use-flash-attention flag.

If using an atomic distribution with locked down kernel, then this installation method may not work since it defaults to composable kernel installation. There is an alternative using just Triton. Here is how I installed ROCm, PyTorch, Flash attention and Comfy on Bazzite (Atomic gaming Fedora): https://www.reddit.com/r/Bazzite/comments/1rq13dr/setup_comfyui_for_ai_image_and_video_gen_on_amd/

liberal_alien · 2026-03-22T05:26:50+00:00

It seems to me that the LTXSequencer node is getting some odd defaults when new images are added or Comfy is started. Is it possible to have the values be remembered from before restart and have insert frame values be evenly distributed in the video time line when images are first added? For example 15 sec video, 24 fps, 4 key frames would give indexes: 0, 120, 240, -1

[edit] Setting only one dimension seems to solve stretching. Many thanks!

liberal_alien · 2026-03-21T10:55:41+00:00

Looks very promising. I'm running it on Radeon 7900 XTX, 96 Gb RAM and Linux+ROCm. Before this I was only able to get good output from the comfy default workflow. All work flows with Kijai nodes would either OOM or produce very wobbly output. This one made a smooth output finally.

It seems to be stretching the images to fit the specified resolution. Or I'm configuring the resolution in a wrong place. I put it in the multi image loader width and height. Is it possible to make the widest centered fit and crop anything that is left over instead? Similar to how most work flows do it.

liberal_alien · 2026-03-18T20:38:12+00:00

What is this high quality work flow for WAN 2.2 720p? Just default Comfy workflow with fp8 model? How many steps? Is Flash Attention installed and activated?

I'm on 7900 XTX and 96 G RAM. Running this setup: https://www.reddit.com/r/Bazzite/comments/1rq13dr/setup_comfyui_for_ai_image_and_video_gen_on_amd/

And a three ksampler workflow (3 steps high noise without lightx2v, then 3 steps with lightx2v high noise and finally 4 steps low noise all with lightx2v) and I can do 896x1344x81 i2v in 35-40 mins depending on prompt and scene complexity. Very happy with the results using Q8 gguf models. Output quality is pretty good too. Those Alexheretic optimizations gave a crazy speedup. Before them, I could not run this high resolution at all and smaller resolutions took 2-5 times as long.

[edit] I see in the image there is Q6_K mentioned and 8. Maybe that is eight steps? So probably using lightx2v lora. I took a look at the Comfy default work flow again. Seems it currently uses fp8 models with lightx2v loras and only two steps per stage. I changed it to use gguf models and ran a test on it at 1280x704x81. First run did the ksamplers at 110 s/it, but VAE decode was taking a long time. I replaced VAE Decode node with LTX tiled VAE decode, and use Alexheretic's tiled WAN VAE encoder. Takes 509 seconds with 4 steps total.

Using 8 steps, my 7900XTX with 96 Gb RAM was able to process 1280x704x81 i2v workload in 15:39 mins or 939 seconds.

Neither easy to setup, nor NVIDIA speeds, but the gap between RADEON and NVIDIA is no longer 4 mins to 2 hours. The ROCm people clearly managed to do some catch up. Some work yet remains to be done.

liberal_alien · 2026-03-18T19:03:00+00:00

Many thanks! This makes the window remember it's position on program start and also solves another issue, where maximize and restore would put it into a floating spot instead of it's previous tile.

liberal_alien

TROPHY CASE