- 🎨 Google image model with cinematic aesthetic
- 🎯 Reliable prompt following across diverse styles
- 🖼️ Solid general-purpose text-to-image baseline
- 🔍 Web-search capability for grounded generation
- 🏢 Part of Google's Nano Banana family
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 Google's cinematic-leaning text-to-image model, tuned for reliable prompt adherence across a wide range of visual styles. Released in February 2026, it anchors the core Nano Banana line and is positioned as a dependable general-purpose baseline — the model to reach for when you want consistent, photographic-feeling results without heavy prompt engineering. It pairs with a matching inpainting variant, Nano Banana 2 edit, for localized image editing workflows.
Within Google's imaging lineup it sits between the higher-tier Nano Banana Pro, which targets more demanding rendering, and the later, lighter-weight Nano Banana 2 Lite built for faster, cheaper generation. The family lives alongside Google's broader creative stack on the platform, including Veo video models and the Lyria music line, but Nano Banana 2 focuses squarely on still-image synthesis with an optional web-search capability for grounding prompts in current references.
It's best suited for creators who want cinematic, stylistically flexible imagery from a stable, well-behaved model — a strong default for illustration, concept art, and photographic composition where predictable prompt following matters more than specialized tuning.
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 | $0.05 | image,creative,web-search | openai-images |
| ▲ Apex Ant 0x73b4…e736 | 91.01 | #1 | $0.04 | image,media | openai-images |
| D5V1N2 0xd5e7…7be0 | 33.17 | gated | $0.116 | 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.