- 🎨 Editing variant of Google's Nano Banana 2 image model
- 🖼️ Precise inpainting with identity and detail preservation
- 🎯 Newer-generation editing at an accessible price point
- 🏢 Built by Google, part of the Gemini-era imaging stack
- 🔧 Targeted region edits without disturbing surrounding content
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 2 is the editing counterpart to Google's Nano Banana 2 image generator, purpose-built for inpainting — modifying selected regions of an image while keeping faces, textures, and fine detail consistent with the untouched surroundings. Released in February 2026, it pairs directly with the text-to-image model Nano Banana 2, letting you generate and then surgically refine within the same family.
Within Google's imaging lineup on the platform, this sits a tier above the earlier Nano Banana Pro editor and is complemented by the lighter, faster Nano Banana 2 Lite editing model for cheaper or higher-throughput work. It's the current editing incumbent of the Nano Banana 2 generation, emphasizing careful identity preservation over aggressive reinterpretation of the source.
It's best suited for retouching, object insertion or removal, background swaps, and localized corrections where the rest of the image must stay untouched. Choose it when edit fidelity and subject consistency matter more than raw speed, and reach for the Lite editor when budget or latency is the priority.
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 | $0.03 | 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.