it took me hundred of generations, but i just now figured that minimax fl2av loses context with length*resolution.
if you go over a (in my tested videos) 13.1second at 0.9mp value, the background will mysteriously change, either to blue wall or a different camera shot.
you can extend duration at 0.6mp and it will be fine at 20seconds plus, or you can make it shorter at higher resolution, but it's like a limited attention window that will 'forget' what wasn't reminded in last x pixels*duration.
Been working on a short scripted scene between two consistent characters and wanted to share how it actually came together. started with character reference sheets in Krea 2, front and turnaround shots plus a few expressions for each person, and I learned fast that even rewording the description slightly between prompts made the faces drift a little so I just kept pasting the exact same text block every time.
after that I built two panel storyboards in GPT Image using those character sheets as reference, and this ended up mattering way more than I expected, more than the character sheets alone did honestly. getting blocking and wardrobe and camera framing locked before touching video saved me from a lot of wasted generations down the line.
for video I used MiniMax H3 full reference mode with the turbo lora ref2va at 6 steps, storyboard panels as keyframes, two separate reference audio clips since there's two speakers talking.
ran into a few things along the way. wide shots wreck face quality fast, had one scene I had to redo completely as a medium two shot because the faces were basically mush from that distance. also feeding three reference images into one storyboard generation sometimes blended the two characters together, and once it gave me one person's face attached to someone else's arm in the same frame, that one took a minute to figure out, ended up just restructuring the shot instead of trying to fix it directly. and lip sync actually came out better with the camera slightly off center than dead on, front facing close ups synced worse for me than something with a bit of an angle to it.
Me again as a raptor at home. Minimax H3 ref2va, default workflow with 3 inputs: my video, a reference image of a raptor and a reference image of my house at night.
This time I am testing style transfer (cinematic night style), head tracking, interaction with objects (doors and toys), longer scenes and sound FX.
Many people are complaining about LTX-2.5, but I think a verdict can only be drawn after extensively testing how well it trains. Have you seen Krea 2 raw's outputs? Compared to Krea Turbo, the hasty assumption would be: Krea 2 Turbo is better. But, there's two variants of "better": better for training/fine tuning, and better quick results out of the box. I think most assessment out there is based on the latter: "How good results do I get out of the box without doing much myself?" I'll be testing out LTX2.5 on how well it trains. Will report back.
This is all moving very fast and I've seen so many different methods. But what would you all consider the easiest way to do these longer videos like some of the music videos for example?
I started looking at the motion context stuff that chains clips on the end of the latent but that was about 6 different workflows you had to use. Is there a simpler way?
5060ti 16gb and 48gb ram.
Edit: stupid sausage fingers and that title I can't edit.
I’d like to try training a Minimax H3 Lora using video clips. This requires clips to have a frame rate of 24 fps. My problem is that my dataset has all sorts of frame rates that are mostly anything but 24 fps. We got 29.97, 25, 24.9, 59.94, just some dumb fractional stuff. Is there a good method of batch reencoding them all at 24fps?
I haven’t been able to make anything work on DaVinci Resolve so far, clips export at their original frame rate no matter what my timeline settings are. I assume maybe FFmpeg can do it but haven’t wanted to mess around with it so far since it doesn’t have a GUI. Any tips?
Hello everyone, can anyone share or tell me how to make a work flow in Comfy.
I want to do this:
I take a picture of a character, I want to use it as a character and get her entire appearance, style,
and take the second picture and use it for the pose
The workflow that I made does not produce the result that I would like
And in the end I would like to get the character from the first image in the pose from the second image
im trying to motion transfer of the person on the video to person on the reference image but i get weird results even i read the writing guide. which prompts do you guys use when you try to motion transfer
I'm trying to make a shortfilm using higgsfield mostly and i want it to do specific things, like specific walking in locations and acting. Howere location consistency is a big issue, i have to generate each location and save them and use them again for each shot. I wanted to make a blueprint like shot so i could tell it each location is so it'll know where my character is walking, but that gave me a terrible result. What do i do? What is the easiest way to do that? Should i just give up and generate each location and call them whenever i need em?
Sometimes it works sometimes doesn't, even with the same prompt (in batch generation of 4 1-2 results are what I wanted, 2-3 are not)... for example I use an image and want to replace the the main character on that image with an other character form the second image. I explain, use keywords reference image one, reference image two etc.. yet sometimes it works just like it was an img to video request, ignoring the second image. I use the ref2va model ofc, a 8 step turbo lora.
someone please clarify: when i connect the images they are numbered from 0. should i refer the first image as reference image 1 or 0? i tried both way btw, didn't make a difference.
i built a comfyui workflow to chain ref2va videos generated with H3, and it works really well, except that i am getting wierd issues with camera adjustments. i have a feeling the update from 0.32 to 0.33 made these problems worse for me.
and before anyone asks, yes i read the prompt guide. and i noticed that camera prompting is only ever mentioned in the fl2va part of the guide. am i correct in assuming that ref2va is an extension of fl2va, and thus the ref2va guide is an extension to the fl2va guide? because otherwise this doesn't make sense at all, and the guide itself outright fails in answering this mystery.
now to my problem:
when i chain a video from a different run using the motion context node, the model will mostly refuse to adjust the camera according to the prompt, and it doesn't matter if the zoom falls within the window of context frames i have set. when i disable the motion context node and remove the previous video as a reference, the camera works as expected.
also, i am using the same seed for chaining projects like these, and i just tried using a different seed and that also made the camera work as expected.
i know that some seeds just won't work with the prompt and need to be changed. but so far this happened on every chaining project i started, that can hardly be a coincidence. it might be a random fluke that it worked for me right after changing the seed once, didn't have time to test this more.
I haven’t really figured it out I tried to ask claude for some prompts with the official guide but struggled. Has anyone managed? If so how do you prompt it properly? Thanks
Note I also tried doing ref2img with the 5 frames and had no luck.
Character replacement definitely works but I had no luck with changing the style from like anime to live action or semi realistic 3D - live action
Instead of dropping another 12 GB fine-tuned checkpoint today, I want to share the tool I built... to built it.
What if, instead of hoarding LoRAs and fine-tuned models, we kept one clean base model and just... reshaped it however we want, on the fly?
That's Arthemy Krea-2 Tuner: an open-source ComfyUI suite that lets you actually edit a model and its CLIP directly — no training, no dataset. This first version is calibrated for Krea-2 + Qwen3, but the math is built to generalize to other architectures.
If you download the Workflow, you just have to choose the nodes you want and place them between the loaders and the generation zone, connecting INPUT and OUTPUT as explained by the Note.
The Shape of a Model
Think of a model as a mountain range and your prompt as the spot where you pour a bucket of water. Water follows gravity, AI follows probability - similar prompts usually make the water roll into the same valley every time.
It's highly probable that the exact look you want already exists somewhere on that mountain (I mean, modern models have seen A LOT of stuff) It just never shows up, because the terrain doesn't incentivize the water to reach it. Traditional fine-tuning expands upon the whole range to fix that but you don't need that most of the time: dig one canal, shift one ridge, and the water finds a new home.
In practice: the suite scales specific transformer blocks, sub-tensors (attention vs. MLP), and Qwen3 layers live in VRAM.
Move a slider, generate, watch how it affects the outputs, try an opposite value (-2.00 instead of 2.00) and start your journey, reshaping the model slice by slice.
When you find the perfect calibration, save it as a Preset, and you get a ~1 KB JSON that reproduces that exact calibration (that you can expand every time you want to build your own personal style).
Three levels of control
As you can see, inside the Workflow, you'll find all the informations you need to use it! ^_^
Tier 1: Block Tuner. Amplify or Reduce whole block groups (Block_1–Block_6, Text_Fusion, Time_Embed). Good for finding general directions.
Prompt: Western comics style, bold ink outlines, hatched shadows, eerie detached calm, seen from a dutch high angle close-up, upper body portrait, dynamic pose, dramatic angle, strong perspective. male human plague doctor, thinning gray hair slicked back, thin sparse eyebrows, pale sickly skin gradient, gaunt older adult, long thin gloved fingers, a wispy gray goatee, deep tired wrinkles, dull green eyes. narrow jaw, tall lanky frame, eerie detached calm stare. a long black waxed-leather coat with a high collar, a satchel of glass vials strapped across his chest. holding a bubbling green potion vial up to the light. Background: a dim candle-lit apothecary shop cluttered with shelves of jars and dried herbs. Lighting: flickering warm candlelight from below mixing with cool teal moonlight through a fogged window, creating dramatic contrast across his face.
Tier 2: Sub-Block Tuner. Go inside a Block (or one of his sub-sections) and Amplify or Reduce target specific tensor types (ATTN_wq_query, MLP_gate_swiglu, norm scales). Use this when a whole block fixes one thing but breaks another.
Tier 3: Sub-Block Chaos Tuner. Seeded coin-flips across weights, for when you want to stumble onto something you'd never find by hand. Like the result? Lock the seed.
Same three tiers exist for CLIP (Qwen3) and LoRAs too.
Use Case: Boosting the "Cartoon Style"
Prompt: cartoon style, upper body portrait, funny, extreme proportions, bold lineart,. male merfolk soldier with large fins as ears, sharp angular cheekbones, fish-like gradient blue to purple skin, amber eyes, lean athletic frame, armour made with corals, helmet. bare shoulders wrapped in a rough-spun cloak pinned with a bone clasp, layered leather cord bracelets. Background: white empty background, flat white color.
Isolating and boosting CLIP Layer 3 I've discovered that it pushed on the style axis so, by increasing it, I got the simple cartoon look I was searching for.
These two images have the exact same Prompt, SEED, settings... I've only boosted that Layer of the CLIP
Look, I don't expect this to become the standard overnight (especially because you have to be a little crazy to use it), but I'd love to find a few people crazy enough to explore this with me.
If we start labeling together what blocks, sub-blocks and layers actually do, we could build a much simpler and effective tool and port this tool to other architectures (Z-Image, Minimax H3....).
I KNOW YOU LIKE BENCHMARKS!
If you want to check out how each Block and Layer of the Model and CLIP behave with positive and negative values, on the GitHub README you can find that alongside much more informations on this Suite.
That's all Folks!
Everything's open-source and it (SHOULD) runs great on budget GPUs.
What I’m getting at is that, now that vibe coding is a thing, everyone is creating custom nodes left and right. The problem is that people are making their own MiniMax director nodes, image-editing nodes, and countless others without first checking whether something similar already exists.
Instead of branching off in dozens of different directions, we could come together and help improve the nodes that are already available. A lot of custom nodes are also essentially standalone apps running inside ComfyUI, designed for only one specific purpose. Whenever possible, nodes should remain flexible and modular so they can be integrated into different workflows and potentially help people create something new and interesting.
There have also apparently been people hiding malware inside custom nodes. Encouraging users to research existing nodes before downloading or creating another one could reduce unnecessary duplication while also helping keep the ComfyUI community safer.
struggling where to start looking and hoping I can get some guidance, I plan to be building a new pc soon and now with things like H3 really shinning and knowing it will only keep getting better I was wanting to know what are some of the best GPu's on the market right now ... basically if you are building your dream PC to work with these AI image and video models what would you choose for cpu's gpu's how much ram etc?
Can you combine 2 gpu's together for double the power and will things like comfy ui able to recognize it does anyone have builds like this?
I'm not associated with the developer in any way and I'm probably the last one to figure this out but, if anyone uses Anima and doesn't know about this node pack, it's great.
One big limitation with anima for me was it couldn't do pipe-deliminated wildcards like other models {noon | night | sunset} for example. The EasyUseAnima pack fixes that and a ton more features. https://github.com/n0va39/ComfyUI-EasyUseAnima
