QGO PromptingReal

8317°

#realistic #sci-fi #3d #comics #clothing #poses

NSFW

NSFW model. Its pictures are hidden while NSFW is off; turn NSFW on to see them.

Run this model

Offers / Ads

Easy Creator (Prism) Web

Unlimited · flat fee

Best for beginners. Describe what you want in a chat and the picture comes back, no learning curve.

PirateDiffusion Telegram

Unlimited · flat fee

Images and video from a chat, with short commands. The most convenient tool for Telegram users, with a web companion.

Pro studio (SpyGlass) Web

Unlimited · flat fee

Best for power users. Full control over models, settings and workflows in a browser studio.

Discord bot (Vector)

Unlimited · flat fee

Best for communities. Add it to your own server and run any workflow from a channel.

Unified Editor Web

Unlimited · flat fee

One screen for every model and workflow: prompts, references, edits and video, built into your Graydient account.

Civitai Web

Pay per use

Generate on Civitai's own site; every image is paid for with Buzz credits.

Local apps

Requires setup

Set up local programs if your computer has capable hardware.

ModelDuel Web

Pay per use

Generate the same prompt on up to 50 checkpoint/base models at a time.

Rent a GPU on the cloud

Graydient Cloud GPU

Unlimited · flat fee

Flat fee, unlimited use. This model installs with one click.

RunPod Cloud GPU

Charged by the minute

Rent a GPU by the minute and set the model up yourself.

Created by

QEGo

on Civitai

QGO Prompting Real V1 by QEGo is a full model checkpoint merge, a base art style for your realistic image creations. The creator's civitai notes state that it was designed for minimal prompting, but as this is a checkpoint merge and the example image prompts are very long, I would take it with a grain of salt... use strong negatives and a booster like fc-portrait for better results Example prompt /render /parser:new /sampler:dpm2m /size:768x832 /seed:1862676218 /guidance:6 (candid frontal closeup close up body portrait of a ((Russian woman:1.2)) model (with long Blonde Pixie Cut Haircut:1.2),…QGO Prompting Real V1 by QEGo is a full model checkpoint merge, a base art style for your realistic image creations. The creator's civitai notes state that it was designed for minimal prompting, but as this is a checkpoint merge and the example image prompts are very long, I would take it with a grain of salt... use strong negatives and a booster like fc-portrait for better results Example prompt /render /parser:new /sampler:dpm2m /size:768x832 /seed:1862676218 /guidance:6 (candid frontal closeup close up body portrait of a ((Russian woman:1.2)) model (with long Blonde Pixie Cut Haircut:1.2), (posing in Dazzling Ballroom with Shimmering Dance Floor and Twinkling Lights during Snow Level:1.1), (wearing Glamorous Hollywood Film Star Fashion with Satin Gowns and Fur Stoles:1.2), at dark night, moonlight, (naughty), (Saluting:1.1), Dappled light Hair light, (bright flash photography:1.2), Deep reds aesthetic, (focus on the eyes), (hard shadows, pitch black brackground, unlit, dark theme, dim lighting, deep contrast:1.1), (background in focus), (wearing Futuristic Post-Apocalyptic Survivor Attire with Tattered Leather Jackets and Goggles:1.2), analog film grain overexposed blurry polaroid) [[[ comic, illustration, painting, airbrushed, glossy, render, animation, 3d shaders, monochrome, sepia, deformed, text]]]

Creator notes

Hello world Let's get real It's been a while since the last update, and this iteration is quite different than the last. That's not to say it is necessarily groundbreaking compared to anything else on this website (it's a merge after all), but I've tried to focus on a couple of very specific things: - A high amount of realism without any use of LoRAs or embeddings. Having a good basis provides a lot of room to go crazy with those later. - Functional with a limited/small negative prompt. Similarly, a small negative prompt often makes for the most realistic outputs. It is always possible to write your novel, or add embeddings in there along the way. - Consistency in poses / hands / other features within these constraints. - Decent control over light and darkness through prompt alone There are great LoRAs out there for lighting / noise offset, but there is already some great functionality by default. - Responsiveness to the wildest lists of wildcards ChatGPT has to offer. I like to have random lists of locations, time periods, clothing/materials, concepts, all generated (and embellished) by your local GPT. Recommended VAE (not included): -High base resolutions are advised: such as 640x896 for a portrait format -If possible use hires.fix or a similar implementation: a denoise of 0.3~0.5 will do well in most situations various give good results. is the one used in all examples here, but there are other great options. -Don't feel obligated to use time consuming samplers such as the one in most examples. I was suffering from a short bout of SDE Karras addiction when generating the examples, but I have since come back to 2M Karras @ 15~20 steps, which is usually my baseline and more than fine on its own (even with hires.fix). *Note that some of the example prompts can generate nudity, prompt against this to prevent it. For actual examples of nudity you can check out the album uploaded separately. **The model in the metadata is QGO-3002a, which is the same as QGO-PromptingReal-v1

16,279 downloads · 1,280 likes on Civitai

SHA256

1EABE50675224173CBDB2C96C745E55790BCA4620C06B406D6935DB0516FDA19

QGO PromptingReal Popularity Trend

Heat score, last 12 months

Heat score

8,317°

This week

▼

0.5%

8,319° then, 8,317° now

This month

▼

2.3%

8,328° then, 8,317° now

Past year

▼

27.2%

8,459° then, 8,317° now

7,000°

Floor

The scale runs from 0° to 9,999°. Everything below 7,000° is kept for models no source reports on yet, which carry a stand-in number there so lists stay complete. 7,000° is where measured data begins: a model with real data but almost no downloads sits at the floor, and the measurements fill the degrees above it. The floor says nothing about the model; only the degrees above it do, and they are what separates one model from another.

+1,280°

Civitai downloads

16,279 downloads of this exact version on Civitai. Downloads are the heaviest ingredient and are counted on a log scale: ten times the downloads adds the same 300°, so a model with a million downloads is not a thousand times hotter than one with a thousand. The six download sources share that one term, split between them in proportion to their counts.

+466°

Likes

1,280 likes and thumbs up across the sources. A like weighs half a download, on the same log scale.

+30°

Adoption rate

About 2 downloads a day, measured between two readings of the sources, never guessed from a lifetime average. Speed weighs a quarter of the download term, so a fresh surge shows without letting a one-day spike outrank years of use.

+150°

Full model

+150° because this is a full model: a checkpoint, the weights themselves. A LoRA or an embedding is an add-on to someone else's weights and does not outrank a checkpoint of equal popularity.

−609°

Age

−609° because the SD15 weights came out in 2022. Every model inherits the age of the weights it is built on: 150° a year, up to 750°, and it keeps growing until then. Without it the top of the list would be 2022 and 2023 checkpoints on the strength of downloads that had years to pile up.

Show detailed breakdown

Every number on this site can be checked. This model's heat score is 8,317°, and here it is built one ingredient at a time, with the running total after each: the floor, the degrees each source adds, the bonus for the kind of model and what the age of its weights takes away. The colors are the bands of the chart above. The glossary at the end defines every term.

1
Start at the floor.
Why 7,000° and not zero: the scale runs from 0° to 9,999°, and the part below 7,000° is reserved for models no source reports on yet, which carry a stand-in number there so the lists stay complete and never outrank a model with data. 7,000° is where measured data begins. A model with real data but almost no downloads sits here; everything that follows is measurement, and the room above the floor holds ten tenfold steps in downloads at 300° each. The floor is the same for every model, so it decides nothing; the degrees above it do.
7,000°
running total
2
Add the downloads.
16,279 download-equivalents in all, from Civitai downloads. Ten times the downloads adds the same 300°, so size matters but never runs away with the score.
+1,280°
8,280°
running total
3
Add the likes.
1,280 likes and thumbs up, at half the weight of a download.
+466°
8,746°
running total
4
Add the adoption rate.
About 2 downloads a day right now, measured between two readings, at a quarter of the weight.
+30°
8,776°
running total
5
Bonus for a full model.
A checkpoint carries the weights themselves; add-ons do not outrank one of equal popularity.
+150°
8,926°
running total
6
Take off the age.
The SD15 weights came out in 2022: 150° a year, up to 750°, growing until then.
−609°
8,317°
running total
=
The heat score.
Where this model stands on every list of this site. Nothing else adjusts it.
8,317°

Glossary: the terms used here

Heat score: One number for how much a model is used and wanted right now, from 0° to 9,999°. Every list on this site that says hottest is sorted by it and nothing else.
Floor: The 7,000° every model with real data starts from. The scale runs from 0° to 9,999°; the part below the floor is reserved for stand-ins (models without data), so that a model with data always ranks above one without. The floor is the same for everyone and decides nothing; the degrees above it are the measurement.
Download-equivalents: Everything the score treats as a download, added up: downloads themselves, each torrent seeder as 1,000, each AI Horde image and each run on a generation site as one.
Log scale: Counting by tens, not by ones: going from 1,000 to 10,000 downloads adds the same degrees as going from 10,000 to 100,000. It keeps giants from crowding out everything else.
Likes: Thumbs up and likes from every source, worth half a download each on the log scale.
Adoption rate: How many downloads a day a model gets right now, from the difference between two readings of a source. A quarter of the weight of the download term.
Measured and estimated: Measured means two readings of a source exist and the difference is real. Estimated means only today's total is known and the past is spread over the model's life; the site says which one it is showing.
Seeder: Someone who keeps a copy of the weights online for others to download over a torrent, or a hosted mirror doing the same. Each one counts as 1,000 downloads.
AI Horde: A volunteer network that generates images for free on donated computers. The number of images it has made with a model is public, and each counts as one download.
Generation sites: Sites that host their own copies of a model and let people generate with it, such as PixAI, SeaArt and Yodayo. Their downloads count like Civitai's and each generation run as one download.
OpenRouter tokens: A text model served through an API, such as Claude or GPT, has no weights to download, so its usage is measured in tokens: the pieces of text it read and wrote through OpenRouter, a gateway many apps use, over the last 30 days. Every 10,000,000 tokens count as one download. Source: OpenRouter (openrouter.ai/rankings), CC BY 4.0.
Full model (checkpoint): The weights themselves, the file that generates on its own. It gets a bonus because add-ons depend on it.
LoRA and embedding: Small add-on files that steer someone else's weights toward a style, a character or a concept. They cannot run alone.
Family and weights: The base a model is built on, such as SD 1.5, SDXL, Flux or Wan. Every model inherits the release date of its family's weights.
Age: Degrees taken off for how long ago the family's weights came out: 150° a year, up to 750°. It keeps old downloads that had years to pile up from freezing the top of the list.
Family boost: A small, bounded nudge for LoRAs of a family this site is pushing forward right now, always listed in the breakdown.
Stand-in score: A stable number below the floor given to a model no source reports on yet, so lists stay complete. It never ranks above a model with data.
New! (grace period): A model less than 7 days old shows New! instead of a score and holds no place in the rankings. Its score is computed from day one, but a model one day old grows faster than anything, so without the wait the week's #1 would always be whatever came out yesterday rather than what held up for a week.
Trend: How a model's growth over a period compares with the typical model's growth over the same period. Faster than typical reads as a rise, slower as a fall.
Typical model: The middle of the catalog: half the models with a figure grew faster over the period, half slower.

How this model's popularity has moved against the rest of the catalog: its growth in downloads, likes and usage over each period, measured against the typical model's growth over the same period, with its heat score at the time. Above the typical growth reads as a rise, below it as a fall. The past is reconstructed from today's totals, the model's first day and its measured download speed where two readings exist; a model that did not exist at the start of a period shows n/a.

Example renders

NSFW

Prompts and settings shared by the people who made these renders on Civitai. Pick a render to see how it was made.