Nano Banana 2 (Gemini 3.1 Flash Image) can ground generations on live web context—not just training data. That matters for skylines after renovations, seasonal events, and product launches where “last year’s Google Image” is wrong.

Five-part prompt skeleton

Identity — named subject or place (“Eiffel Tower from Trocadéro”).
Composition — where the subject sits in frame.
Style — photoreal, illustration, etc.
Reference context — “match current lighting installation” or “winter 2026 crowd levels”.
Text (optional) — quoted strings for signage.

Temporal anchors help: “late afternoon, February 2026”, “during Olympic overlay branding”. Without a time hint, the model may average outdated photos.

Example: travel editorial

The Eiffel Tower from the Trocadéro terrace, full structure centered, empty fountain plaza foreground, photorealistic, soft golden hour haze, match current tower lighting as of winter 2026, small sign reading "Trocadéro" in white sans-serif

Try Nano Banana Workflows

Example: product in real city context

A matte black wireless earbuds case on a café table, Shibuya crossing visible but softly blurred through the window, rainy March 2026 evening, neon reflections, commercial product photo, 85mm look

When grounding fails

Issue	Try
Generic stock look	Name a specific viewpoint + date
Wrong season	Add weather + month/year
Hallucinated signage	Short quoted text only

Access paths

Gemini app for conversational edits; AI Studio when you need model picker and API keys. Grounding behavior is the same family—word your brief like a location scout, not a tag cloud.

Workflow tip

Generate in 1K for layout proof, then rerun at 2K/4K once composition locks. Pair with reference uploads when you need a exact product silhouette on top of a grounded background.

Prerequisites and setup

To leverage live grounding features, you need an active developer account with access to the Gemini 3.1 Flash Image model family. Standard free tiers often lack the specific web-grounding parameters required for temporal accuracy, so verify your subscription level includes experimental imaging tools. Ensure your browser supports WebGL acceleration, as the preview renderer relies on local hardware compositing before final generation.

Install the latest MidassAI CLI or prepare your API environment variables if working programmatically. For non-coders, the web-based Studio interface handles authentication automatically, but you must enable the "Live Context" toggle in the settings panel. Confirm you are selecting the Nano Banana 2 variant specifically, as earlier iterations default to static training data without external search capabilities. This ensures the engine queries live indices rather than relying on frozen datasets.

Extended prompt workflow

Define the temporal boundary: Start your string with a hard date constraint to force the search engine to ignore archived content. Use syntax like [Date: Post-2025] or [Season: Winter 2026] at the very beginning of the prompt block to set the retrieval window.
Layer specific geographic markers: Instead of just city names, include recent infrastructure changes. For example, specify "near the new Hudson Yards observation deck" rather than just "Manhattan skyline" to trigger fresh image retrieval regarding construction status.
Set lighting and atmospheric conditions: Describe the weather as a variable, not a static state. Use phrases like "overcast with wet pavement reflections" to ensure the grounding engine pulls recent meteorological data matching the location's typical climate for that month.
Refine resolution and aspect ratio: Append technical tags like --ar 16:9 and --quality 2 after the natural language description. This separates artistic direction from engine parameters, preventing the model from confusing dimensions with subject matter during the grounding phase.

Common mistakes

Vague temporal references: Saying "recent" or "new" confuses the search index because these terms are relative. Fix: Use specific months and years, such as "October 2025," to lock the retrieval window and prevent outdated stock imagery.
Overloading with text: Asking for complex paragraphs on signage causes hallucination within the grounded scene. Fix: Limit embedded text to three words maximum and keep it in quotes for strict adherence to the visual layout.
Ignoring local events: Failing to account for festivals or construction leads to empty scenes that look fake. Fix: Add context like "during Coachella setup" to populate the background with relevant temporary structures and crowd densities.

Try this in MidassAI

Ready to test live grounding without configuring API keys manually? Open the Studio interface to access the pre-configured Nano Banana 2 environment. Paste your temporally anchored prompt into the main input field, ensure the grounding switch is active, and hit generate to see how real-time data alters the composition compared to static models. This sandbox allows you to iterate on date anchors quickly without burning production credits. Visit https://www.midassai.com/studio/nano/ to start your session immediately.

Nano Banana 2 Web Grounding: Prompts That Use Real-World Context