- 🆕 OpenAI's text-aware image model, released December 2025.
- 🔤 Crisp typography, infographics, diagrams, and multi-panel layouts.
- 🧠 Built-in reasoning and world knowledge infer scene context.
- 🎯 Improved realism, prompt adherence, and editability versus prior generation.
- 🔧 Region-aware editing preserves composition across multi-step workflows.
- ⚡ Flexible quality–latency tradeoffs for fast or high-fidelity output.
- 🔒 Declines to generate identifiable real people without consent.
- 👁️ Natively multimodal: accepts text and image inputs.
OpenAI is an American artificial intelligence research organization headquartered in San Francisco, structured as both a for-profit public benefit corporation and a nonprofit foundation. The lab developed the GPT family of large language models, the DALL-E image generation…
Explore 27 more models by OpenAI →GPT Image 1.5 is OpenAI's text-to-image generation and editing model, released in December 2025 and exposed through the OpenAI API and ChatGPT. It is a natively multimodal system that accepts both text and reference images, integrating visual and language context to leverage strong world knowledge—for example, inferring that a scene set in Bethel, New York in August 1969 refers to Woodstock without explicit prompting.
Compared with the earlier GPT Image 1, OpenAI describes major improvements in realism, prompt accuracy, and editability. Text rendering is a particular focus: where earlier models treated text as visual patterns, GPT Image 1.5 renders crisp lettering, consistent layouts, and strong contrast, making it well-suited to infographics, diagrams, UI mockups, and marketing materials. The model also adds robust facial and identity preservation for character consistency and region-aware "deterministic" editing, so a single object can be changed while preserving camera angle and lighting.
A companion inpainting variant, GPT Image 1.5 edit, supports image editing through the same API. OpenAI later succeeded this line with GPT Image 2 in 2026; both remain selectable in the image-generation API.
Limitations noted by OpenAI include latency on complex prompts (up to about two minutes) and occasional imprecision in text placement and clarity. Use requires API organization verification, and the model declines to generate identifiable real people without consent.
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 | $0.13 | image,creative | openai-images |
| ▲ Apex Ant 0x73b4…e736 | 91.01 | #1 | $0.10 | image,media | openai-images |
| D5V1N2 0xd5e7…7be0 | 33.17 | gated | $0.301 | 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.