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Nano Banana 2 is Google’s speed-oriented image-generation and editing model, known in the Gemini API as gemini-3.1-flash-image. It combines conversational editing, improved text rendering, reference-image capabilities and optional Google Search grounding. It is not the newest Nano Banana release as of August 18, 2026: Nano Banana 2 Lite launched later. But Nano Banana 2 remains the more capable general-purpose choice when quality, complex edits or higher-resolution output matter more than maximum speed.
Hands-on tests found it capable of convincing edits and legible text-heavy graphics, but also prone to incorrect facts, misread instructions and weak face composites. It is useful for rapid visual iteration; treat its output as a draft, not a reliable source of facts or a production-ready image without review.
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- No Cost & No Subscriptions
- Unlimited Generation of Images
- Incredibly Realistic Images
What Nano Banana 2 is—and whether it is still the latest
“Nano Banana” is Google’s consumer-facing name for Gemini’s image-generation capabilities. Nano Banana 2 launched on February 26, 2026, as the public name for gemini-3.1-flash-image. It is a general-purpose model for generating and editing images, built on Google’s Flash model family. Google says it brings together capabilities such as image editing, text rendering, subject consistency and web-grounded generation with Flash’s emphasis on speed. Google’s developer announcement and model-selection guide describe its intended role.
The word “latest” needs a date. Nano Banana 2 was Google’s newest image model at launch, but Nano Banana 2 Lite arrived on June 30, 2026. Lite is newer and optimized for low latency and cost; Nano Banana 2 is the more capable generalist. “Newest,” “fastest” and “best for a demanding image task” are different criteria.
| User-facing name | API model ID | Current role |
|---|---|---|
| Nano Banana 2 Lite | gemini-3.1-flash-lite-image |
High-throughput, speed- and cost-oriented generation |
| Nano Banana 2 | gemini-3.1-flash-image |
General-purpose generation and editing |
| Nano Banana Pro | gemini-3-pro-image |
Higher-end, complex visual work |
| Original Nano Banana | gemini-2.5-flash-image |
Earlier-generation model |
These are API model names; the Gemini app and other Google products can have different controls, limits and availability. Google’s image-generation guide describes the current family and model-selection roles.
Where to try it and how to make an image
In Gemini
Google announced Nano Banana 2 across Gemini, Search AI Mode and Lens, AI Studio, the Gemini API, Vertex AI and other developer products. Rollout and features vary by country, account, subscription and product. Google’s launch announcement described expansion to 141 additional countries and territories and eight additional languages; that does not mean every feature is available to every user everywhere. Google’s launch announcement lists its rollout channels.
Rank #2
- Instant anime art generation in just seconds.
- User-friendly design, no artistic skills required.
- AI-powered creation from simple text descriptions.
- Multiple image dimensions for wallpapers and social media.
- Intuitive home screen for effortless creativity.
- Open Gemini on the web or in the app and start a conversation.
- If the image-generation control (a banana icon in the interface reported at launch) is available, select it; otherwise, ask Gemini directly to create an image.
- For an edit, attach the reference image and describe what should change and what must remain unchanged.
- Specify the subject, setting, composition, style and important constraints. For revisions, point to the specific element that needs correction instead of restating the entire prompt.
- Review the result closely before downloading, sharing or publishing it.
The exact interface can change. In WIRED’s February 26, 2026, report, Nano Banana 2 was the default image model in Gemini at launch; Google AI Pro and Ultra subscribers could select Nano Banana Pro from the three-dot regeneration menu for specialized work. WIRED’s hands-on report describes that workflow.
For developers
Google lists the model in AI Studio, the Gemini API and Vertex AI. AI Studio is an entry point for experimenting; API use is a separate developer route with its own billing, quotas and controls. Google’s announcement said API access requires a paid API key. Check the live Gemini API pricing page for current rates and terms rather than assuming consumer access and API access work alike.
What it does well
Conversational editing and reference images
Nano Banana 2 can generate from text and edit using reference images, allowing a user to request scene changes, object substitutions, background changes or style adjustments across successive turns. Google highlights improved consistency for people, faces and objects. That means it can help preserve a subject through edits—not that it guarantees exact identity or pixel-level control. See the model documentation for the API’s stated capabilities.
Text in images
Google says Nano Banana 2 improves precision text rendering and supports more languages. That can make it more useful for posters, memes, labels, diagrams, advertisements and infographics than image models that routinely garble lettering. Legible text still does not make a graphic’s claims accurate: check every date, number, name and label before using it.
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- Turn text into stunning AI-generated images instantly
- Supports styles like Anime, Cyberpunk, Ghibli, and more
- Choose from 1:1, 16:9, or 9:16 ratios
- Save, share, or delete creations with one tap
- Full-screen viewer for detailed image exploration
Search-grounded visuals
The model can use Google Search grounding, including text and image results, to inform generated visuals about real-world or location-specific subjects. This can help with a visual concept based on a place or current context, but retrieval is not verification: the information can be stale or misapplied, and the image can introduce its own errors. Google explains grounding in its developer announcement.
Resolution and aspect ratios
The API documentation lists 512-pixel, 1K, 2K and 4K output options, with 1K as the default. Google also describes wide and tall formats, including 1:4, 4:1, 1:8 and 8:1, alongside common ratios such as 1:1, 16:9, 9:16, 21:9 and 9:21. These are API capabilities, not a promise that every consumer interface exposes every option. Google’s model documentation gives the API specifications.
What hands-on tests revealed
In WIRED’s February 26, 2026, hands-on report, the model showed both useful image fidelity and consequential failures. These examples are observations from that review, not a controlled benchmark of speed or accuracy.
A polished weather infographic with wrong details
The generated graphic looked polished and its text was comparatively legible, including weather information and a disclaimer. But it used incorrect dates and apparently outdated weather context. After the reviewer challenged it, Gemini revised the graphic with updated information. The practical lesson is to verify every factual element independently; a grounded, professional-looking image is not an authoritative data source.
Rank #4
- Text To Image
- Set Wallpaper
- Word in to Art Generator
- Ai Art Generator
- World of Ai
A convincing edit that misread the request
For a hot-tub edit of a selfie, Nano Banana 2 recreated small source details, including jewelry and parts of a shirt design. It misunderstood “wrinkled from sitting in a tub” as making the person look much older and retained the shirt despite the broader scene request. Reference fidelity can coexist with a semantic mistake, so inspect whether the model changed the intended things and preserved the rest.
A skiing scene with a failed face composite
A skiing image had some convincing composition and snow effects, and the hands looked more plausible than the reviewer expected from older image models. But the face looked pasted onto a different body, undermining the photorealism. Apparent branding should not be assumed authentic. For faces, action poses and branded details, visual plausibility is not enough.
Across these examples, the useful measure is task reliability, not whether an image looks impressive at a glance. The WIRED review is the source for these specific tests.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choosing between Nano Banana 2, Lite and Pro
| Model | Best fit | Trade-off |
|---|---|---|
| Nano Banana 2 | General creation and editing, rapid iteration, multiple references and work that may need 2K or 4K output | More capable than Lite for complex work, but not a guarantee of factual or identity accuracy |
| Nano Banana 2 Lite | Fast previews, simple edits and high-volume 1K workflows where latency and cost matter most | Optimized around 1K; does not support 2K or 4K and has fewer advanced grounding and multi-reference capabilities |
| Nano Banana Pro | Complex professional tasks where detailed creative control, brand consistency or factual precision is the priority | Google positions it as a premium, slower option rather than the default for quick iteration |
Google recommends Nano Banana 2 for balanced performance, instruction-following and rapid generation, Lite for speed and throughput, and Pro for maximum capability on demanding tasks. Those are product-positioning recommendations, not a guarantee that Pro will be correct or that Nano Banana 2 will fail. For Gemini users, Google said Pro remained available to AI Pro and Ultra subscribers through a regeneration menu at launch; API and cloud access have separate terms. See Google’s Nano Banana 2 announcement and Lite announcement.
Best Value
- AI Art Generator
- Image Creation AI
- AI-Powered Image Design
- Creative AI Graphics
- AI Image Maker
API limits and cost considerations
For the API model, Google lists text and image/PDF inputs, image and text outputs, a 131,072-token input limit and a 32,768-token output limit. Batch API and Search grounding are supported; function calling, URL context, code execution and Google Maps grounding are not listed as supported capabilities for this image model. These specifications should not be treated as guarantees for Gemini’s consumer interface. Consult the model page for current API details.
Google Cloud documents approximate output-image token consumption of 747 tokens at 512 pixels, 1,120 at 1K, 1,680 at 2K and 2,520 at 4K; it notes that other input and output modalities can incur additional charges. Those are Cloud documentation figures, not a complete price quote. API costs depend on the live pricing terms and selected output, so check Google’s pricing page before building a budget. Consumer Gemini limits and subscription access are separate from developer API billing.
Google’s developer documentation says Imagen models were deprecated and scheduled to shut down on August 17, 2026. As of August 18, that date has passed; developers choosing a Google image-generation API should consult the current model guide rather than relying on Imagen as an available alternative.
Trust, provenance and responsible use
Google says generated images include an invisible SynthID watermark and describes ongoing use of C2PA Content Credentials to help identify AI-generated content. These signals can support provenance, but they are not a substitute for checking an image’s claims or origin; reposting, cropping, screenshots and platforms that do not expose provenance information can make identification harder. Google describes SynthID and provenance in its image-generation guide and launch announcement.
Do these 3 things before closing this tab:
1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteBecause the model can create realistic images of people, places, brands and current events, consider consent before using someone’s likeness and review brand, disclosure and rights issues before commercial publication. Keep human review in the loop for factual graphics and final advertising. A generated image should not be presented as documentary evidence of an event that did not happen.
Quick Recap
Who should use it?
- Choose Nano Banana 2 for a balance of quality, speed and editing flexibility, especially when you need multiple turns, reference images, Search grounding or 2K/4K API output.
- Choose Nano Banana 2 Lite when you need high-volume, low-latency 1K assets and can give up higher resolution and some advanced capabilities.
- Choose Nano Banana Pro when a difficult professional task justifies a premium option and human review remains part of the workflow.
- Do not rely on any of them unsupervised for live facts, exact identity transfer, legal-sensitive likeness work or final assets where a subtle error would be costly.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
