Ideogram 4.0: A 9.3B open-weight image model
Ideogram 4.0 is a new open-weight image model featuring 9.3 billion parameters. It utilizes a unique architecture that combines a vision-language text encoder with a single-stream Diffusion Transformer. The model is specifically trained on structured JSON captions to enhance image generation capabilities.
- ▪Ideogram 4.0 is a 9.3B parameter open-weight text-to-image model.
- ▪The model employs a vision-language text encoder and a single-stream Diffusion Transformer.
- ▪It is trained exclusively on structured JSON captions with detailed descriptions of image elements.
2 outlets in our directory ran this story, first to last over 1 hour. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.
- ▪ Ideogram v4 is open weights! — r/StableDiffusion
Hacker News (Newest) files mainly under programming. We currently carry 5,306 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Ideogram |
| Canonical URL | https://ideogram.ai/blog/ideogram-4.0/ |
| Publication time | Wed, 03 Jun 2026 16:40:44 +0000 |
| Retrieval time | 2026-06-03T16:52:50.488Z |
| Last seen | 2026-06-03T16:52:52.309Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 6hm0u9qyf_M- · 3 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Technical Model release June 3, 2026 Ideogram 4.0 Technical Details: Open model at the forefront of design Our first open-weight foundation model. A 9.3B single-stream Diffusion Transformer, trained from scratch, with a vision-language text encoder and structured JSON prompts. Authors. Ideogram Team Reading time. 5 min Weights. Hugging Face Code. GitHub Overview Ideogram 4.0 is a 9.3B parameter open-weight text-to-image model. Recent open-weight releases have converged on a single self-attention sequence over text and image tokens[1][2][3], and Ideogram 4.0 follows the same pattern: text and image tokens share the same projections at every layer of a 34-layer DiT. Two design choices distinguish it from peer releases.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Ideogram.
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