- 🆕 Google's professional-tier Nano Banana image model, released November 2025.
- 🎯 Cinematic aesthetic with reliable prompt following across styles.
- 👁️ Strong multilingual on-image text rendering for posters and diagrams.
- 📚 Web-search capability for grounding visuals in real-world information.
- 🔧 Multi-image blending plus a dedicated in-place editing variant.
- 🌐 Multilingual text generation across more than 10 languages.
- 💬 Best guided by descriptive, context-rich prompts with quoted on-image text.
- 🏢 Served through Google's Gemini API.
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 professional-tier entry in the Nano Banana image family. The catalog positions it for a cinematic aesthetic with dependable instruction following across a wide range of styles, making it suited to functional asset production such as posters, diagrams, and product mockups rather than only casual generation. It also carries a web-search capability, letting prompts be grounded in real-world or real-time information.
According to Google's own prompting guidance, the model supports multilingual text generation in more than ten languages and renders legible on-image typography. Google recommends descriptive, context-rich prompts that specify subject, materials, lighting, and cinematic camera terms, with any desired on-image text enclosed in quotation marks.
Within the same family, the lighter Nano Banana 2 is a separate tier in the lineup, while Nano Banana Pro targets higher creative fidelity. A separate inpainting model, Nano Banana Pro Edit, handles in-place edits, so generation and precise local editing are split across complementary endpoints. Together they let users move from initial render to targeted refinement without leaving the Nano Banana lineup.
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 | $0.09 | image,creative,web-search | openai-images |
| ▲ Apex Ant 0x73b4…e736 | 91.01 | #1 | $0.07 | image,media | openai-images |
| D5V1N2 0xd5e7…7be0 | 33.17 | gated | $0.2085 | 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.