- 🎨 Image editing variant of Google's Nano Banana Pro
- 🖼️ Precise inpainting with identity preservation
- 🎯 Strong detail retention across edits
- 🏢 Built by Google
- 🔧 Targeted region edits, not full regeneration
Google is an American multinational technology corporation and one of the world's most valuable brands. A subsidiary of parent company Alphabet Inc., Google operates across search, cloud computing, consumer electronics, and artificial intelligence. Its DeepMind and Google…
Explore 21 more models by Google →Nano Banana Pro is Google's image-editing companion to its Nano Banana Pro generator, purpose-built for inpainting — replacing or refining specific regions of an image while keeping faces, objects, and fine detail intact. Released in December 2025, it pairs naturally with the text-to-image Nano Banana Pro model, sharing the same underlying lineage but specializing in surgical edits rather than full-frame generation.
Within Google's image lineup, this sits at the higher-quality "Pro" tier of the Nano Banana editing line, above the earlier Nano Banana 2 inpainting variant. Its standout characteristic is identity and detail preservation: edits to a region blend cleanly without distorting surrounding content or altering the subject's likeness, which is the hardest part of practical inpainting workflows.
It's best suited for retouching, object removal or replacement, background changes, and localized refinements where you need to modify part of an image while leaving everything else faithfully untouched. For users who already generate with the Nano Banana Pro pipeline, it's the natural next step for polishing and iterating on results.
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 |
|---|---|---|---|---|---|
| ▲ Apex Ant 0x73b4…e736 | 91.03 | #1 | $0.07 | image,media | 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.