Ideogram4
Best for beginners. Describe what you want in a chat and the picture comes back, no learning curve.
Images and video from a chat, with short commands. The most convenient tool for Telegram users, with a web companion.
Best for power users. Full control over models, settings and workflows in a browser studio.
Best for communities. Add it to your own server and run any workflow from a channel.
One screen for every model and workflow: prompts, references, edits and video, built into your Graydient account.
A powerful editor: draw boxes and describe what goes in, and images come to life.
Set up local programs if your computer has capable hardware.
Generate the same prompt on up to 50 checkpoint/base models at a time.
Ideogram 4 text to image. ! Currently very unstable and censored ! Quality settings Instead of steps, you can control quality with /slot2: /slot2:turbo -> fast and rough /slot2:default -> default quality and speed /slot2:quality -> best quality, slowest render This workflow supports two ways to produce the JSON the model expects: (default) Model-assisted (LLM): Enter a short idea in as positive prompt and the system prompt asks LLM to write schema-compliant JSON. You won't see the generated JSON prompt, it is handled only internally. (/slot1:0) Raw input: You may use plain natural language,…Ideogram 4 text to image. ! Currently very unstable and censored ! Quality settings Instead of steps, you can control quality with /slot2: /slot2:turbo -> fast and rough /slot2:default -> default quality and speed /slot2:quality -> best quality, slowest render This workflow supports two ways to produce the JSON the model expects: (default) Model-assisted (LLM): Enter a short idea in as positive prompt and the system prompt asks LLM to write schema-compliant JSON. You won't see the generated JSON prompt, it is handled only internally. (/slot1:0) Raw input: You may use plain natural language, but structured JSON gives the most predictable layout and style control. Incompatible prompt WILL trigger "safety filter", even if prompt is SFW. About the model The model is trained on structured JSON captions (scene summary, style block, background, and optional per-object descriptions with bounding boxes and hex color palettes). Official inference validates prompts against that schema. Guidance uses flow-matching with asymmetric classifier-free guidance (the unconditional pass drops text tokens)—not a separate negative prompt string. Practical strengths: flexible resolution (about 256–2048 px per side), layout via normalized bounding boxes [y_min, x_min, y_max, x_max] on a 0–1000 grid, palette control with hex colors, and strong in-image text rendering when described in JSON. NOTE: If you see "Image blocked by safety filter" it is because of safety training in the model itself and there
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.
