ideogram-oss/ideogram4
Ideogram 4: Open image model at the forefront of design observed · 2026-08-28
Health v2 · maintenance only
54/100
- Activity 90
- Release rhythm 35
- Longevity 6
Flags: no_releases young
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 97
- days_rel: n/a
- days_push: 64
- n_releases_24m: 0
Adoption not part of the score
2766 stars · 286 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Ideogram 4 is an open-weight text-to-image foundation model trained from scratch, with inference code and weights released in Python. It features structured JSON prompting, multilingual text rendering, bounding-box layout and color-palette controls, and native 2K resolution output.
Use cases
- generate images from text prompts
- render legible text inside generated images
- control image layout with bounding boxes
- generate posters and design assets with specific color palettes
- run a state-of-the-art text-to-image model locally on GPU
- generate high-resolution 2k images
When to avoid
- you need lightweight CPU-only image generation
- you only need image editing rather than text-to-image synthesis
- you lack a supported GPU for inference
Facets
library · maturity active
machine-learning image-processing llm-inference artificial-intelligence image-processing deep-learning machine-learning python text-to-image diffusion-model open-weights image-generation typography design diffusers gpu linux
1 source
- readme: https://github.com/ideogram-oss/ideogram4 · fetched 2026-08-28 · 8098c557d82e
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| ideogram-oss/ideogram4 | main | 54 |
For agents
markdown · JSON · MCP: product_card(name="ideogram-oss/ideogram4")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem