Google: Nano Banana 2.1
google/gemini-nano-banana-2.1
Access Nano Banana 2.1 from Google using the Puter.js AI API.
Add to your appModel Card
Nano Banana 2.1 is Google's image generation and editing model, released in October 2026 as the successor to Nano Banana 2 (Gemini 3.1 Flash Image). It improves visual quality, text rendering, subject consistency, and mask-based editing, and accepts up to 14 reference images.
It outputs 1K, 2K, and 4K images, supports configurable thinking levels, and runs at Flash-tier speed. In preliminary Arena rankings it placed #5 for text-to-image (1328) and #6 for image editing (1428), ahead of Nano Banana 2 by 80 and 38 points.
Image output is priced at $0.0336 per 1K image, half of Nano Banana 2, though Google's Nano Banana Pro still produces more realistic images at a higher price. It suits developers who need lower-cost image generation and editing.
Cost Per Image $0.0336
per generation
Configuration 1K:1x1
resolution
Release Date Oct 6, 2026
Add Nano Banana 2.1 to your app
Use Nano Banana 2.1 in your app with the Puter.js AI API, no API keys or setup required.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.txt2img("A serene mountain landscape at sunset", {
model: "google/gemini-nano-banana-2.1"
}).then(image => {
document.body.appendChild(image);
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.txt2img("A serene mountain landscape at sunset", {
model: "google/gemini-nano-banana-2.1"
}).then(image => {
document.body.appendChild(image);
});
</script>
</body>
</html>
More AI Models From Google
Gemini 3.8 Flash
Gemini 3.8 Flash is Google's workhorse Flash-tier model, released September 2, 2026, three weeks after Gemini 3.7 Flash. It's built for long-horizon software engineering, agentic workflows, and multi-step reasoning in professional domains. Google reports it outperforms 3.7 Flash and other frontier models on DeepSWE v1.1 for autonomous engineering tasks, on Vals Finance Agent V2, and on Harvey's Legal Agent Benchmark. It scores 54.9% on HLE-Verified, and completes more than three times as many tasks as 3.7 Flash in Google's long-running, document-heavy workflow evaluations. It accepts text, image, video, audio, and PDF input with a 1M token context window and 64K token output limit, supports function calling and iterative tool use, and has a March 2026 knowledge cutoff. Priced at $0.75 per million input tokens and $3.75 per million output tokens through 2026, it targets teams running coding agents or document-heavy enterprise workflows.
ChatGemini 3.7 Flash
Gemini 3.7 Flash is Google's workhorse Flash-tier model, released August 13, 2026, three weeks after Gemini 3.6 Flash. It's built for coding and agentic workflows, targeting software engineering, web development, and knowledge-dense domains like finance and law. Google reports gains over Gemini 3.6 Flash on several benchmarks. DeepSWE v1.1 rose from 49.0% to 65.3%, FrontierCode 1.1 from 34.4% to 43.6%, and AutomationBench from 17.0% to 30.4%. On FrontierCode 1.1 it scores above Claude Sonnet 5 (42.7%) and GPT-5.6 Terra (41.3%), though GPT-5.6 Terra edges it out on Terminal-bench 2.1 (87.4% vs 85.8%). It accepts text, image, video, audio, and PDF input with a 1M token context window and 64K token output limit. It supports function calling, search as a tool, and computer use, and has a March 2026 knowledge cutoff. It's priced at roughly half of Gemini 3.6 Flash's rate, fitting teams running coding agents or high-volume document processing.
ChatGemini Robotics ER 2 Preview
Gemini Robotics ER 2 Preview is Google's embodied reasoning model for robotics, available through the Gemini API and Google AI Studio. It takes video, images, audio and text, reasons about a physical scene, plans multi-step tasks, and hands actions off to a vision-language-action model, a robotics API, or developer-defined tools through function calling. Google says it can plan its next step while a robot is moving, works with the Gemini Live API, and can monitor a task in video, detect failures and retry individual steps. It also supports multi-robot coordination. In Google's reported tests it reached 91.3% accuracy at identifying when a key event occurred in a video (mean error 0.96 seconds) and 57.4% on progress classification. It is meant for developers building robot planning, success detection and scene understanding on top of the Gemini API.
Frequently Asked Questions
You can access Nano Banana 2.1 by Google through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required.
Nano Banana 2.1 is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.
| Price | |
|---|---|
| Per image | $0.0336 |
Nano Banana 2.1 was created by Google and released on Oct 6, 2026.
Yes — the Nano Banana 2.1 API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Add Nano Banana 2.1 to your app for free
Developers can integrate Nano Banana 2.1 for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.