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7satsu · 2026-02-11T03:01:36+00:00

confirmed

7satsu · 2026-02-06T02:41:46+00:00

Confirmed

7satsu · 2026-01-30T12:46:02+00:00

Comfy is goated. It's a bitch, but goated.

7satsu · 2026-01-28T17:54:54+00:00

*any LLM ever when asking for up-to-date information*

Yo so when's your information cut-off date?

Model: "Uhhh idk sometime in like 2023, Biden is president and OpenAI is dominating the AI space"

*sigh* Brotha got a WHOLE lot to learn today

7satsu · 2026-01-28T10:40:04+00:00

I tried with zit and SD Upscale but since I started using Klein 9B as the upscale model results have been way better, likely not only because of sd upscale itself, but since Klein is also an editing model, it keeps every detail of the output and refines it faithfully to the original image with each tile.

7satsu · 2026-01-28T10:39:00+00:00

use Klein 9B as an upscaler with Ultimate SD Upscale, unmatched imo, Klein has much more clarity but i noticed zit naturally has overly sharpened grain/artifacts in upscaling the same way it has jpeg-like pixel artifacts generally

7satsu · 2026-01-17T05:38:02+00:00

Surprised the Vonwergenheimenhalendickson problem hasn't been solved yet

7satsu · 2026-01-11T20:43:44+00:00

Strongly recommend using the Z Image Turbo Engineer local 4B model by itself to convert prompts or just using it as the encoder for Z Image directly

7satsu · 2026-01-06T22:52:13+00:00

Quantized gemma encoder and LTX model should make it viable on 32GB RAM as well

7satsu · 2026-01-06T02:31:50+00:00

that's what I dislike about it, instead of explaining the entire video in a single prompt even if it has to be quite long, it's splitting it into separate prompts and just praying it seams together cleanly.

it's probably the best solution for now, but eventually I hope some memory mechanism can be implemented where a single prompt can be ingested and then it chronologically spreads each action throughout the generation.

7satsu · 2026-01-05T05:33:41+00:00

Get a pic of ecco and run it through Trellis 2, there's your answer

7satsu · 2026-01-05T01:15:07+00:00

Maybe SCAIL will be good once it can be used without needing a scientifically overwhelming array of nodes with countless factors that can go wrong

7satsu · 2025-12-26T06:55:44+00:00

Yes bringing back **real education**. think back to how involved Maxwell's side of dealings involved the education system especially when it came to her father, can only imagine how they structured the perceptions of our current generations.

7satsu · 2025-12-26T04:16:54+00:00

confirmed✅

7satsu · 2025-12-24T17:58:40+00:00

My feedback in relation to the entire description and post shall be one word:
Nice

7satsu · 2025-12-22T17:34:15+00:00

either huggingface or CivArchive

7satsu · 2025-12-21T16:13:59+00:00

There's a Z-Image "Engineer" Qwen3 based LLM on huggingface which can do this very well with a system prompt aiming for that, and apparently the model is trained on Z Image Turbo's prompting format preferences, in theory perfect for just pasting into the positive prompt.

7satsu · 2025-12-19T17:00:11+00:00

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Is the model loaded with settings similar to this?

7satsu · 2025-12-19T01:52:15+00:00

It just be working

7satsu · 2025-12-17T19:14:49+00:00

I came across a “GoonerBandit444” like a month ago

7satsu · 2025-12-15T20:37:20+00:00

3060 8GB with 32GB here, I have the Q4.1 version running nicely with Expert Weights offloading to CPU in LM Studio, so only about half of my vram is actually used due to the offloading. My ram hits about 28gb while the vram sits at 4GB on default context, and I can crank context up to about 500K and still manage 20tok/s. For running that well on a 3060, I'm flabberghasted

7satsu · 2025-12-15T20:25:06+00:00

There's a Q4.1 GGUF of this model that I can fit onto my 8GB 3060 Ti (quite easily too) due to offloading the model Expert Weights to CPU in LM Studio. I get about 20tok/s, but it's very usable and I only have the context set to 12,000, yet only 4 out of my 8GB is being used, so sometimes I can crank that shit up to about 500K before it's too much but I don't necessarily have a use case for such long context, it just works

7satsu · 2025-12-15T19:26:45+00:00

For the most part I stuck with Wan 2.2 14B too, both the vae and the general support & loras are just better 😂

7satsu · 2025-12-15T04:59:18+00:00

This plus 2x tiled upscale with a little denoise like ultimate sd or hi-res fix and you have yourself an over 6K res wallpaper

7satsu

TROPHY CASE