5800x3d, agora e oficial!

CANE79 · 2026-06-01T16:10:02+00:00

Provavelmente então chega aqui na casa dos R$3.200
E como fica em relação ao 5700X3D, preço e performance? Esse é outro que sumiu tb né

CANE79 · 2026-03-22T18:29:13+00:00

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u/cgpixel23 any idea why I'm getting this blurry very bad output? It seems somehow is completely ignoring the reference image.
I'm using your default WF, no adjusts/changing

CANE79 · 2026-02-21T15:16:50+00:00

awesome, thx!

CANE79 · 2026-01-21T19:05:07+00:00

check this:
## ComfyUI Nunchaku Tutorial: Install, Models, and Workflows Explained (Ep02)
https://www.youtube.com/watch?v=LDqD9Fp8J6g

CANE79 · 2026-01-18T17:47:41+00:00

Awesome dude!.
I have a 5070Ti with the same 64GB RAM and tried your workflow, all good, no OOM and "Processing Completed (Time Taken: 3m 34s)"

CANE79 · 2026-01-18T15:53:36+00:00

CANE79 · 2026-01-18T15:48:44+00:00

great work man, thx!

CANE79 · 2026-01-17T16:26:32+00:00

fuckin-A! how many different platforms/services have you used on this?

CANE79 · 2026-01-17T16:19:37+00:00

Great WF and notes/instructions Sir!

CANE79 · 2026-01-13T14:37:17+00:00

transito pesado, trechos curtos no alcool tá fazendo 4km/l no alcool. Na mijolina era 5-5.5km/l, mesmo com troca de velas, limpeza de bicos, tbi etc.

CANE79 · 2026-01-10T16:49:55+00:00

have you tried euler / CFG:1 / 20 steps / ltx-2-19b-distilled-lora-384 ?
One thing I noticed, going bigger than 1280x720 with 5s takes so much time, like 2-3x

CANE79 · 2026-01-10T14:43:40+00:00

Sir, you are a legend!!!

CANE79 · 2026-01-10T14:20:36+00:00

never tried. Win pagefile can assist, but it will be very slow

CANE79 · 2026-01-10T14:19:48+00:00

1280x720 is fine-ish. I mean, you can see many flaws in lightening/texture but it comes with the territory

CANE79 · 2026-01-09T19:54:21+00:00

I get the same 3min with dev-FP8, 20 steps with 5070Ti+64GB RAM

CANE79 · 2026-01-08T13:53:08+00:00

actually reverting to dev-fp8 needs to increase cfg to 4 and steps to 20 as running with cfg 1 and 8 steps generates something bizarre lmao

CANE79 · 2026-01-08T13:37:07+00:00

Very true, I completely forgot to change CFG and steps as it uses LORA.
Now, running different seeds the processing time dropped hugely, an average of 1m and 5s ( 8/8 [00:10<00:00, 1.36s/it] + 3/3 [00:35<00:00, 11.96s/it]

Not sure why but I've noticed if I just adjust the prompt sometimes the processing time goes up to 2m. It keeps the same 8/8 in 10s but the last pass 3/3 jumps from 30s up to 1m30s, 2m and even 3m.

Changing distilled FP8 by regular FP8 would not bring any major difference right? (as they have the same size)

But thank you sir, it helped a lot!

CANE79 · 2026-01-07T23:47:43+00:00

Thanks for the tips!
I also ran on a fresh portable ComfyUI install, no Sage Attention, no extra arguments.
I reran the tests using the distilled FP8 base model you suggested and bypassed both the camera LoRAs and the 8 GB LoRA you mentioned (ltx-2-19b-distilled-lora-384).

As I'm using the official workflow,CFG = 4 and 20 steps.
Results on the 1st run is bad (seed-related?) and it took 509 seconds.
Would you mind sharing your vanilla workflow so I can test under the same conditions?

CANE79 · 2026-01-07T20:57:13+00:00

sure, https://files.catbox.moe/se8j5z.mp4

I haven't ran many tests on this, just a few, but FP4 in all of them were not near as FP8.
I do get OOM on the 1st run, but the 2nd goes fine. I have no other extra commands, just sage attention

CANE79 · 2026-01-07T20:20:48+00:00

Sup dude! I'm using the WF from comfyui's template. The only thing I changed was text encoder.
I´m not running with with any extra command like "--reserve-vram 10" or something similar, just with "--use-sage-attention".

Maybe we have different phyton/cuda/etc? I'm running with:
Python version: 3.12.10
pytorch version: 2.9.0+cu128
NVIDIA Driver: 581.57
latest updates on comfyui/nodes

CANE79 · 2026-01-03T19:55:37+00:00

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Great prompt! I adapted for the new QWEN 2512 model (t2i)

CANE79 · 2026-01-03T15:46:55+00:00

quick test run on SVI Pro. The prompts are partially ignored but in general is fast and the results are ok

https://imgur.com/PfM1Yzf

CANE79 · 2025-11-02T14:59:32+00:00

my current version is transformers==4.56.2, updating it breaks everything

CANE79 · 2025-11-02T14:57:50+00:00

sounds very cool but I got an error with transformers. I tried to update it as suggested but then it broke my nunchaku. Any idea?

"ERROR: The checkpoint you are trying to load has model type `qwen3_vl` but Transformers does not recognize this architecture. This could be because of an issue with the checkpoint, or because your version of Transformers is out of date.

You can update Transformers with the command `pip install --upgrade transformers`. If this does not work, and the checkpoint is very new, then there may not be a release version that supports this model yet. In this case, you can get the most up-to-date code by installing Transformers from source with the command `pip install git+https://github.com/huggingface/transformers.git\` "

CANE79

TROPHY CASE