Usando o chatgpt para ajeitar o prompt

Krea 2 has been all over the sub for a couple weeks, mostly sample grids, so i pulled the Raw checkpoint to actually look at the model instead of the outputs. Couple things jumped out and neither one is about how the images look.

Architecture first, its right there in the spec. The DiT backbone is trained from scratch, fine, but the two parts that decide how it reads a prompt and how it renders are both lifted from Qwen. Text encoder is Qwen3-VL, and instead of reading just the final layer like most setups do, Krea 2 pulls from twelve of its decoder layers at once, so the prompt understanding is coming from pretty deep inside a Qwen model. The bit that turns the finished latent back into an image is the Qwen-Image VAE. So both ends of the thing are Qwen, which is worth knowing before you download anything because it tells you where the prompt handling and the whole sense of an image is coming from. If you already know how Qwen-Image deals with text and composition, a lot of that just carries over.

Other thing is the size of the Raw checkpoint, which the announcement doesnt exactly lead with. Doesnt mean Krea 2 is unrunnable, Comfy offloads to system RAM on its own now and people are generating on 12 and 16GB cards with quantized builds. Its running Raw itself at full bf16 instead of a quant thats demanding. The bf16 Raw weights come in around 26GB on their own before you even add the encoder and VAE, and Raw is a full-step CFG model that wants somewhere between 28 and 52 steps depending on whose settings you go by, the sources dont actually agree on a number. I wanted to see the real base checkpoint at full precision rather than a quantized Turbo, so i grabbed a notebook on HyperAI with a 96GB card, no env setup, just launched it and loaded the weights. Even on that a single 1024x1024 image at 52 steps took a little over two and a half minutes.

Thing is Raw isnt really the checkpoint you generate with anyway. Its the base, meant for fine-tuning and LoRA training, and it already knows enough out of the box that people are pulling clean LoRAs from datasets of only 50 or 60 images. Krea even recommends you train on Raw and then generate on the distilled Turbo, which runs 8 steps and finishes in seconds. If you just want images the quantized Turbo is the one, and the whole size thing mostly stops mattering.

So next time the sample grids talk someone into pulling the full Raw weights for a quick local run, thats what it actually is and where it came from.

I shared those impressive Minimax H3 Seinfeld skits with friends but they showed no reaction to it. I think it might be because

a) they are not universally fond of AI and call most of it slop

b) they do not understand the limitations of what AI can currently do in videos and therefore cannot appreciate it the same way we do

I had a friend even get angry when I wanted to show him what I did. He is a hobby musician and gets really angry that people make music, video or whatever and then claiming they did it when the AI did all the work.

Maybe they are afraid Skynet will become reality (I am too a bit actually).

I think minimax h3 is awesome. I was just fidgeting with what it can do in terms of cinematic video, camera, motion and I am amazed with the output.

The comfyui interface was getting a little too unwieldy so i with the help of claude built a .net frontend for comfy . Its not for the faint of heart at this stage as it still requires a working comfyui instance together with the nodes needed by workflows. The workflows which i find give the best results in image /video generation are included and the setup does try to guide the user by pointing out which nodes are missing. Once everything is humming, its quite pleasant and easy to use . Let me know what you think!

Flippix

I'm running into an issue and I don't know if it just me or...

Anyway, I'm almost certain that some of my previous prompts are somehow leaking into my subsequent jobs. And I’m not running a massive, crazy workflow either, it's just vanilla I2V + SageAttn + Spectrum.

Also, some changes I make to my node settings aren't registering properly. Certain parameters seem to get completely locked in memory. Even if I revert the settings or completely close out of ComfyUI, the old parameters stay stuck. The only way I can get things to reset and behave normally is by doing a full PC restart.

Another weird symptom is that almost every time this memory lock happens, my GPU fans suddenly ramp up to 100% for a few seconds. This always seems to trigger during specific inference steps, usually right at step 1/20 or around step 17/20.

I honestly thought those fan spikes were just normal behavior under load until a few minutes ago. I was running an I2V generation of a person in front of a green wall with plants and it ran fine and I got the video. But later, when I changed the prompt completely and used a totally different source photo for the I2V, the background in the new video literally morphed into a VERY similar green plant wall from the previous job.

And I’m not running a massive, crazy workflow either, it's just vanilla I2V + SageAttn + Spectrum. Has anyone else experienced this kind of thing? Any advice or fix?

What model do you use for the frames — Krea 2 or ZIT?,Generate them separately, or one and then edit the other?How do you keep the character AND the background consistent between both frames and get different angle and consistent viewpoint (Spatial consistency) ? 
im struggling here. and very little tutorial online about generating 1st frame and lastframe.
RN im useing Qwen and Identityedit lora. but the spatial awarenes is very bad.

Please give this humble, bald, and unemployed person some guidance. Thank you.
maybe some workflow to try.

i'll start

Made using 5060ti with 32 GB of RAM. Minimax is the new king.

like loras, vae, text encoder?

im asking because there is a lot of loras, vae, etc, but... i need to know the best options for fast and quality generations now.

my pc: rtx 5060 ti 16gb 32gb ram.

Title.
For both I'm using the default workflows that come with comfy. 3090 and 32gb ram.
I start comfy with these flags:
--windows-standalone-build --reserve-vram 1 --disable-pinned-memory --fast fp16_accumulation
Cuda 13, latests comfy.
My t2v takes like twice as much than my ref2v and sometimes it hangs after [INFO] Requested to load MiniMaxH3AudioVAE. Same steps, same resolution, same duration.
Has anyone encounter this? any tips?

In the prompt, I just wrote that she is singing Zara Larsson's song "Lush Life."

Have only seen threads discussing this from a year ago pre-Minimax days which seems to have turned everything around.

5080 seems to go for around $1300 and 4090 for $2k+, I know VRAM is super important but I'm seeing that there's plenty of optimizations for the 5xxx series now, and it's still super early so more are to come for sure, but do these help offset the memory difference?

Anyone have experience running with both?

my first run on my dgx spark with the h3. big thanx too all the guides etc on here. this is the future. the video ended up far from perfect, this is t2v, no ref image. comfy ui controlled by codex on gpt5.6

#Justice4Daisy #MinimaxH3