- 🆕 Latest text-to-image model in Ideogram's generation lineup.
- 🎯 Listed among Ideogram's officially available models.
- 💬 Generates images from text prompts.
- 👁️ Works with Character Reference for consistent characters.
- 🔧 Integrates with Ideogram's broader image toolset.
- 🌐 Usable online and through the Ideogram API.
Ideogram is a text-to-image AI company founded in 2022 by Mohammad Norouzi, William Chan, Chitwan Saharia, and Jonathan Ho. The team set out to build a generative image model with a particular strength that many rivals struggled with: rendering legible, accurate text directly…
Ideogram V4 is a text-to-image generation model in Ideogram's lineage, following the earlier Ideogram 1.0, 2.0 and 3.0 releases. It appears among the options documented in Ideogram's published list of available generation models, indicating it is a current, selectable model for image creation.
Like recent Ideogram releases, V4 works alongside the broader Ideogram toolset, including Character Reference, which lets you define and reuse a character so facial features, hairstyles, and other traits stay consistent across multiple images. The model can be used online at ideogram.ai and integrated through the Ideogram API.
Note that this catalog lists no sibling entries for cross-linking, and independent benchmark evaluations were not available among the consulted sources. Several commonly cited V4 differentiators could only be traced to an unofficial repository, so they are omitted here; the description above is limited to details that could be confirmed from Ideogram's own documentation rather than comparative performance or capability claims.
This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.
| Seller | Reputation↓ | Routing | $ / img | Categories | API |
|---|---|---|---|---|---|
| Venice.ai Proxy 0x1f22…18c9 | 100.00 | #2 | $0.03 | image,creative | openai-images |
| ▲ Apex Ant 0x73b4…e736 | 91.01 | #1 | $0.02 | image,media | openai-images |
| D5V1N2 0xd5e7…7be0 | 33.17 | gated | $0.0695 | image,creative,router,fallback | openai-images |
"Best price" and the seller table are live AntSeed catalog data (advertised $/1M tokens — or $ per generated image for unit-billed image models — not settled amounts). Reputation = on-chain trust (0-100). "Routing" = the SDK's default buyer routing (what the VPR desktop app ships with): a trust ≥ 60 gate on the effective reputation, then cheapest-first among routable sellers; live failover state (per-peer cooldowns) is buyer-side runtime and not included. Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase. "Usage on AntSeed" counts only settlements whose buyers share the per-model split on-chain (metadata v2/v3, opt-in), so every usage figure is a lower bound.