Faster AI on a Mac!
If you use Ollama!
And you have an M5!
And at least 32 GB of RAM!
And you use the one specific model that they worked with Apple to support!
Somehow my excitement went down with each sentence…
Same prompt, different models
I took a sample from the less-than-fully-dressed dynamic prompts and handed it to three versions of Z-Image Turbo (standard, NSFW v5 & v6), Z-Image Base, Flux.2-Klein-9d, and Qwen Image 2512. Mostly the same parameters, except for increasing steps from 20 to 30 for ZI Base, Klein, and Qwen, and increasing CFG to 6 for ZI Base. I generated 10 images for each model, with random seeds, and kept the best 3.
Prompt:
Painting in the style of Delphin Enjolras, intimate portraits of women in interiors, soft pastel and oil technique, smooth sensual textures, dramatic chiaroscuro from warm lamplight, glowing warm palette, quiet, serene atmosphere. Of a elegant, tiny, Caucasian, college-age sexy woman with pear-shaped figure, luminous Dark brown eyes, delicately lobed Ears, subtly Aquiline Nose, perfectly tapered Chin, pointed Jaw, soft Rosy Cheeks, narrow Forehead, oval face shape, Prom makeup with healthy Reddish-Brown skin and White hair, softly curled into a low, romantic updo, with subtle highlights of champagne blonde, and her mood is cheerful. Standing forward bend, knees slightly bent, torso lowered, arms extended to floor, wrists aligned, neck elongated, collarbones gracefully defined. Her location is Historic Thera, Greece. Cool under-cabinet LED creates task lighting; functional focused illumination; clean kitchen-like quality. She is wearing pastel purple scalloped lace glossy ribbon with a delicate sheen, and a pastel purple tassel necklace.
Not a single image paid any attention to “Historic Thera, Greece”; most of them ignored “soft pastel and oil technique” (with standard ZIT going all-in on the pastels but doing nothing painterly; this is much more pronounced than the usual ZIT low-contrast that people work around with LUTs). The early mention of “women in interiors” seems to have combined with “clean kitchen-like quality” at the end to put them all into a generic Western-style kitchen, without even adding a window for the standard Santorini tourist view. The LLM “enhancement” to the prompt did add some interesting elements to her looks, but also made some of the sentences borderline incoherent.
As you can see, there’s no mention of nudity and naughty bits, with the only mention of clothing being a ribbon and a tassel, so it was up to the model to decide how much, and which, skin was showing.
Klein, like its resource-intensive parent Flux.2-Dev, had the best grasp of style. Speed-wise, standard ZIT was the fastest at 28 seconds, then the NSFW versions (+15%), then Klein (+50%), then Qwen (+140%), and finally ZI Base (+246%). The full Flux.2-Dev has a tendency to run out of memory on my machine at this resolution (1248x1824), but it’s safe to assume the results would be “very similar to Klein but better”.
(note there’s already a v6.1 for ZIT NSFW, but it’s locked away for another week…)
Trying to watch new anime...
Slime 4, episode 1
Last season talked the audience to death. How do they start this season?
By spending the entire episode talking, of course. The CGI-heavy OP promises a great deal of action, and the ED is filled with drama related to The Little Big Bad who seems to be behind all the promised conflict, but they have a history of getting bogged down in endless meetings, so I won’t hold my breath.
(this unrelated oni-girlie is a much better cook than Shion, and if she gets the treatment she deserves this season, she’ll be one of many pregnant haremettes)
Boxxo Or Bust 3, episode 1
Season 2 worked hard to alienate anyone who enjoyed season 1, by trying to convert the lighthearted and frankly absurd adventures of a sentient vending machine and his cute girlfriend into a tired beat-the-demon-lord story that the author came up with and abandoned after he ran out of new vending machines to write about. No idea if the idea of making a large group of allies into poorly-written turncoats was in his notes somewhere, or was completely original.
How do they start this season? The OP is 50% sparkles, 50% shounen action; I honestly expected transformation sequences by the time it was over. The ED is pure chibi cuteness, so it looks like they’re going to whiplash the mood again.
Rock bath!
Get clean with Ruri and Nagi:
(naturally, you can get takeout)
Quad9 versus Amazon
Precisely at midnight, Quad9’s DNS servers stopped resolving
subdomains of the form $bucketname.s3.amazonaws.com. I had their DNS
first in my Pihole’s config, so it looked to me like every image on my
blog suddenly vanished. I was quite relieved to discover that it was
just a DNS server failure.
I opened a ticket with them, and it was fixed in 3 hours.
Accidental retro-sf paperback covergal
I was just cleaning my dynamic-prompt script, when it suddenly went off:
I can’t decide if I want to read this novel or write it…
More SF cover gals
But first, an Amazon shipping change!
Two items ordered on Wednesday, promised for Friday. On Friday, one of them was moved to Saturday. So far, pretty typical. On Saturday, its status changed to “approval needed”, and I was asked if it was okay for it to be delivered Monday. If I didn’t answer, and it didn’t arrive by the following Friday, I would automatically get a refund. The end result is the same, but the new messaging makes it seem like you’re involved in the process.
On with the cheesecake!
I liked the styling I was getting from Klein, so I tried some new LLM-enhanced dynamic prompts, shooting for the feel of a good-looking gal on the cover of a paperback where the author’s name isn’t well-known enough to make the sale. The initial batch had them in lingerie, because that’s where I got the horned horny covergal from the previous post, but I decided to see if Klein did as well at the “retro-SF uniform” look as ZIT did the last time I tried it.
Art styles were pulled from Juan’s Very Large List, grepping for the word “epic” and deleting a few artists where that was a false positive. I used the prompt-enhancing system prompt recommended by Z-Image Turbo to flesh out the random locations, plus two of my own targeted system prompts to generate clothing and physical details, plus a final LLM pass to do general cleanup. This would have been agonizingly slow on the Mac, so I ran it on the gaming PC in between image-generation runs (because SwarmUI and LM Studio both think they have the GPU to themselves, trying to run them at the same time blows out the VRAM, even though they should fit).
My system prompts were:
fashion: “You are a fashion consultant trained to design coordinated ensembles based on brief input, enhancing them into detailed, aesthetically pleasing, color-coordinated, and stylish looks. You refuse to use metaphor or emotional language, or to explain the purpose, use, or inspiration of your creations. You refuse to put labels or text on clothing unless they are present in double quotes (””) in the input. Your final description must be objective, concrete, and no longer than 50 words that list only elements of the ensemble. Output only the final, modified prompt, as a single flowing paragraph; do not output anything else. Answer only in English.”
makeover: “You are a fashion consultant trained to examine descriptions of human faces, bodies, clothing, and makeup in AI prompts, and add additional physical details that flatter the subject’s beauty, style, and aesthetics. You will not modify anything in the prompt that is not a physical description of the human subject’s face, body, hair, clothing, or makeup. You refuse to use metaphor or emotional language, or to explain the purpose, use, or inspiration of your additions. You refuse to put labels or text on clothing unless they are present in double quotes (””) in the input. Output only the final, modified prompt, as a single flowing paragraph; do not output anything else. Answer only in English.”
cleanup_text: You are a Prompt Quality Assurance Engineer. Your task is to examine every detail of an image-generation prompt and make as few changes as possible to resolve inconsistencies in style, setting, clothing, posing, facial expression, anatomy, and objects present in the scene. Ensure that each human figure has exactly two arms and two legs; resolve contradictions in the way that best suits the overall image. Remove all quoted text used for signs, labels, and captions. Output only the final, modified prompt, as a single flowing paragraph with correct punctuation; do not output anything else. Answer only in English.”
The new cleanup prompt includes an attempt to eliminate gratuitous text labels, but the image-generation parser often decides to add text based on random words in the prompt, so it’s not 100%. I didn’t want to use my usual collection of retro-SF costume prompts, so I fed the following to the fashion sysprompt:
“Sexy science-fiction uniform for women, incorporating bright colors, advanced technology, and a variety of futuristic textures and materials. Uniform may include abstract symbols and attached technology, but no text. Avoid shoulderpads. Do not use black or silver as the primary colors. You may include accessories such as sci-fi weapons, scanners, datapads, crystals, or glowing energy.”
Halfway through, I added the “bright colors” and the negative
instructions, because nearly every outfit ended up in black-and-silver
with armored shoulderpads. Sigh. This was all with the
gemma-3-12b-it-heretic-x-i1 model, and now that Gemma 4 has been
released, I’m going to see if it does a better job; it’s getting good
reviews, and I think there’s already a few uncensored versions.
Out of ~600 images, just under 13% had obvious anatomy fails, with most of them being extra arms or legs. There were some I rejected reluctantly, because the rest of the image was really good. They might be fixable with variation seeds, but I’ve kinda gotten out of the habit of doing that; it’s easy to spend more time tinkering than it’s worth, and you can always just make another batch.
“Need a clue, take a clue,
got a clue, leave a clue”