Dear Fellow Capsuleers,

I am Veetor Nara, the “stats guy” / “charts guy” in the EVE_NT team, working in the Alliance Tournament every year. This time I would like to do something additional to give the viewers additional things to root for during viewing the finals.

https://preview.redd.it/w59bb3a5ivph1.png?width=2594&format=png&auto=webp&s=d2efd92a94b1ff8b899c996254461b3343275d95

So, let me present: the EVE_NT Fantasy Alliance Tournament!

What is the Fantasy AT?

During the feeders, we’ve recorded each pilot, team match, and their success. (You can see those here.) We a

Hey All

I have been working on a new GGUF format for Krea 2 / similar diffusion models: Q8_CR.

I wanted to have something, which is...

• Targeting firstly Ampere and Turing architecture GPUs (RTX 20xx and 30xx cards)
• Uses ComfyUI's new INT8 kernel
• Narrows the (already very small) quality gap between INT8 and FP16 checkpoints

So, GGUF Q8_CR stores eligible linear weights as pre-rotated INT8 weights with FP32 per-row scales, while retaining 1D, small, and precision-sensitive tensors at high precision. It is not regular Q8_0 dequantized back to FP16 for every operation: when the required ComfyUI backend is available, it uses ComfyUI's native INT8 ConvRot path.

I tested it w

I've not been finding the existing harnesses completely comfortable for me, so I put something together myself, focusing on comfort and reasonable security* (Yes, I will explain it).

So here it is, Truss:

The starter screen, rather simple.

Installer: https://github.com/truss-harness/Truss/releases/tag/v0.1

Source: https://github.com/truss-harness/Truss (Apache 2.0 license)

The harness and its tools packaged as MCPs (including a bundled browser, Camoufox, th

Hi all,

Probably for some others me, there is a more conservative budget when it comes to their AI hobby. I've been collecting basically e-waste and could now assemble something partially working from them.

Specs:

$ neofetch
            .-/+oossssoo+\-.               molbal@...
        ´:+ssssssssssssssssss+:`           -------------
      -+ssssssssssssssssssyyssss+-         OS: Ubuntu 26.04 LTS x86_64
    .ossssssssssssssssssdMMMNysssso.       Host: Supermicro X9DR3-F
   /ssssssssssshdmmNNmmyNMMMMhssssss\      Kernel: 7.0.0-27-generic
  +ssssssssshmydMMMMMMMNddddyssssssss+     Uptime: 3 hours, 15 mins
 /sssssssshNMMMyhhyyyyhmNMMMNhssssssss\    Packages: 1

I'm training a Krea2 image editing LoRA and ran out of GPU budget. Datasets and nodes are open, looking for contributors

When you look at what Krea2 can do natively and compare it to what Flux2 Klein, Qwen Image Edit and similar models deliver. I think Krea2 has the architecture to support good reference-image-guided editing — give it a photo and a prompt, get back a pixel-anchored edit — but nobody has shipped a fully working patch for it yet. There are other projects (Identity Edit Lora, Ostris's patch) I started building one, got further than I expected, and then ran out of GPU budget at step 7500.

Everything I built is open, including the code and the training dataset. I'm posting

Hi lads,

I've done some work to convert Krea2 to GGUFs. It should come in handy for GPUs with <8GB VRAM.

Get the GGUF loader nodes from here: https://github.com/molbal/ComfyUI-GGUF

Get the converted models from here: https://huggingface.co/molbal/krea2-gguf

Q4_0 uses 7573MB on my GPU, but GGUFs are generally easier to offload if you have less VRAM.

Here is one example (I accidentally left the bf16 in the name, that just meant that I took the BF16 weights to convert from):

https://preview.redd.it/742shbsyta9h1.png?width=720&format=png&auto=webp&s=c5d0a67c8ae8c374ec1e36105779ff470f43e826

Sorry t

Hello Lads,

I've fiddler around with the Ideogram 4 GGUF support in Comfy (on my fork only) and tried to introduce _K quants in the hopes of getting better compression and/or higher quality output. While I could make that work, it involved a very heavy performance penalty of about 5x slower inference, so I scrapped that path.

However, Q5 quants work nicely, for someone who has just a tiny bit more VRAM available and find its outputs better.

Nerd Stuff

Here is memory usage in my tests. You can mix and match quants for the 2 models. You can even mix and match it with nvfp4-gguf, but I did not test that:

https://preview.redd.it/1k6nau1x8i7h1.png?width=1640&format=png&auto=webp&s=f38c6

Hi lads,

I am currently 8GB VRAM enjoyer and was not satisfied with the nvfp4 model (it always had weird artifacts), and I had an hour to spare so I forked the GGUF nodes and patched them up to load the ideogram ggufs correctly from here:
https://huggingface.co/leejet/ideogram-4-GGUF

Usage:

Just replace the model loader nodes with GGUF loaders, and that's it. If someone is really impatient, it might work until the maintainer does a proper update (or thinks this is fine and merges my PR)

If you want to try the nodes, clone my fork: https://github.com/molbal/ComfyUI-GGUF

The workflow is in t

Goedemorgen/Jó reggelt,

I am a Hungarian IT architect currently living in the Netherlands. I see many posts here discussing digital independence, so I wanted to share a project I just completed that argues for exactly that concept, but specifically focused on companies rather than individuals.

I recently released a book titled Beyond the Public Cloud: Architecting Private, Secure, and Sovereign AI for the European Enterprise.

I know there is deep skepticism around AI in this community (Which I mostly share). But I also think it the technology is here to stay and is genuinely useful in some cases. If it is here,

Hello,

I bought an older dual xeon computer. Fujitsu Celsius R920, the motherboard is proprietary and is called D3118. The CPUs are the original Xeon e5-2670 ones. The seller is trusted and verified the computer works before he shipped it to me. After I delivered I saw some damage to it during transit despite proper packaging. (large thick cardboard box, the components inside were all tied down or padded, outside the box was double bubble wrap, extra cardboard padding extra foil around the edges/corners)

The front grille was damaged and there was a cd reader which got dent, so for now I removed all those. I checked as much as I could with my eyes the PSU, CPUs, memory, a 2.5" sata SSD,

I have an Asus ROG Zephyrus G15 2022 model and I also have a setup with an external GPU, which does not play nice with my laptop.

I have a:

- Asus ROG Zephyrus G15 2022 model (GA503RS, with Ryzen 7 6800H CPU and RTX 3080 GPU, and the ASUS-provided BIOS and USB power delivery firmware updated)

- A desktop RTX 3090 card (Inno3d rtx 3090 x3)

- A dedicated power supply for the GPU (Cooler Master V850 Gold v2)

- An ADT-Link U3TG 1.6 adapter (Verified running the latest firmware)

- A short thuderbolt cable

I have it all plugged in, scraped off the previous display driver in safe mode, installed a new nvidia driver, got it recognized, but anytime I begin to use the GPU more heavily (Mac

I have a G15 2022 model (Excuse me for writing in the G14 subreddit, this is much more active and the models are similar) and I also have a setup with an external GPU, which does not play nice ever with my laptop.

I have a:

- G15 2022 model (GA503RS, with Ryzen 7 6800H CPU and RTX 3080 GPU)

- A desktop RTX 3090 card

- A dedicated power supply for the GPU (Cooler Master V850 Gold v2)

- An ADT-Link U3TG 1.6 adapter (Verified with the latest firmware)

- A short thuderbolt cable

I have it all plugged in, scraped off the previous display driver in safe mode, installed a new nvidia driver, got it recognized, but anytime I begin to use the GPU more heavily (Machine learning training f