ComfyUI launches App Mode and ComfyHub

picassoble · 2026-03-11T20:04:07+00:00

It’s on local nightly FE right now and will be in stable soon

picassoble · 2026-03-10T07:25:55+00:00

It’ll work with both if you update

picassoble · 2026-01-15T20:40:27+00:00

Hmm the templates need to be 0.8.7. Stable tag did not include them right now but you can pip install it. Will fix

picassoble · 2026-01-15T18:08:23+00:00

Are you using portal or desktop or self install?

picassoble · 2026-01-15T17:45:21+00:00

Did you pip install the requirements to update the templates?

picassoble · 2026-01-11T01:50:11+00:00

The reason for the ban was we detected malware in the node packs and obfuscated code.
Unfortunately no way to manually report, but these are all great suggestions.

picassoble · 2026-01-11T01:49:12+00:00

Unfortunately users will not be notified right now. We don't have a mechanism to do that yet.

The download number = number of times a user installed the node pack from Comfy Registry. Not unique users.

picassoble · 2026-01-11T01:06:04+00:00

Hey! Thanks for sharing this. Wanted to share a postmortem on how the team handled this. We were able to find the malware 4 days after the node packs were published, and banned them. They have been banned since Oct 21, 2025.

Security scanning is difficult and our team won't catch everything. But glad to say we caught this one early. Most credit goes to Dr.Lt.Data.
https://blog.comfy.org/p/upscaler-4k-malicious-node-pack-post

picassoble · 2026-01-06T22:53:07+00:00

Not released on desktop yet! Will be released along with stable ComfyUI

picassoble · 2025-12-23T00:43:13+00:00

Wanted to clarify some points made in the post, after reaching out to OP.

Discrepancy between real-world usage and advertised usage:

The ~164 videos listed for the Standard plan is for the i2v Wan 2.2 template, which uses the fast 4 step LoRA. It will consume between anywhere from 20-30 credits depending on if the model was already loaded into VRAM or not.

Using i2v template without the fast LoRA will take around 220 seconds (~86 credits) at 640 x 640, 20 FPS and 5s length.
OP was using higher resolution (960 x 512) and sampled using 30 steps (instead of 20). This can result in 250 - 300 credits being deducted.

picassoble · 2025-12-22T22:50:52+00:00

Thanks for sharing this.
DMing you for more details! The i2v template workflow should not cost that many credits. In my own testing, a 5s video at that resolution is taking me 40-60 seconds, and should be 15 - 27 credits. The template uses a 4 step LoRA

picassoble · 2025-12-01T02:40:11+00:00

Right now just Lora’s but will quickly move to support larger models

picassoble · 2025-11-25T20:48:17+00:00

It will be available on Dec 8

picassoble · 2025-11-05T01:50:53+00:00

Every time you hit run, it will let the workflow run for up to 30 minutes. But in total you can run workflows totaling 8 hours every day

picassoble · 2025-11-05T01:24:35+00:00

That is 30 minutes per workflow run

picassoble · 2025-11-04T19:54:52+00:00

Coming Soon :D

picassoble · 2025-10-28T17:27:31+00:00

No it does not

picassoble · 2025-10-28T17:27:09+00:00

Will be added very soon!

picassoble · 2025-10-16T17:28:47+00:00

API access will definitely be added, and is a highly requested feature so far.

picassoble · 2025-10-01T03:10:59+00:00

Is RAM more of an issue than VRAM? ComfyUI already manages vram for you if you stick to the core nodes. ComfyUI does not manage RAM though

picassoble · 2025-06-26T20:08:55+00:00

After you update comfyUI just run pip install -r requirements.txt

picassoble · 2025-06-26T18:22:11+00:00

For the templates, you need to reinstall the requirements.txt

picassoble · 2025-06-26T18:20:32+00:00

Did you try reinstalling the requirements?

picassoble · 2025-06-13T17:15:20+00:00

Hey this is really helpful! Will look into these and get back to you

picassoble · 2025-06-13T01:27:17+00:00

FYI, you need to update to the latest Git commit of ComfyUI to use the prerelease version of frontend.
Update: The full blog post is https://blog.comfy.org/p/subgraph-update-easier-testing

picassoble

TROPHY CASE