Nano Banana 2.1

Nano Banana 2.1 — AI Image Generation and Editing

What is Nano Banana 2.1?

Nano Banana 2.1 (gemini-nano-banana-2.1) is Google's high-efficiency image generation and conversational editing model, a generally available update to Nano Banana 2 built on the Gemini image stack. It turns text prompts and up to 14 reference images into polished visuals at 1K, 2K, and 4K, and it edits existing photos from plain-language instructions. Its headline gains over the previous generation are sharper visual quality, stronger prompt adherence, better multi-turn character consistency, and markedly cleaner text rendering and infographic layout.

Key Features

• •Legible in-image text and accurate infographic layout for diagrams, posters, menus, and marketing assets.
• •Multi-image fusion with up to 14 references — object fidelity for up to 10 objects and character consistency for up to 4 people.
• •Instruction-driven editing that changes targeted elements while preserving the rest of the frame.
• •Wide and panoramic aspect ratios (including 4:1 and 8:1) at 2K and 4K, with the earlier tiling artifacts fixed.
• •Adjustable thinking levels (minimal, medium, high) and Google Search grounding for real-time facts.

Best Use Cases

Reach for Nano Banana 2.1 when words and layout matter: labeled scientific diagrams, data infographics, product and packaging mockups, social and ad creative, and editorial covers. In testing it rendered a six-label volcano cross-section with every callout spelled correctly, fused a toy robot and a vintage camera from two separate references into one scene, swapped a pancake breakfast for blueberry waffles while keeping the table untouched, and produced a seamless 4:1 library panorama.

Prompt Tips and Output Quality

Put any wanted in-image text in quotes and name each element you expect to see. Use thinking_level high for dense layouts and multi-reference compositing, and medium for straightforward edits. Pick 2K for a strong everyday default and 4K for print; PNG keeps text crisp while JPG suits photographs. When editing, address references by position and state explicitly what to keep.

How to Use Nano Banana 2.1

Nano Banana 2.1 generates and edits images from a prompt and up to 14 reference images. The prompt is your main lever: name every element, quote any text you want rendered, and say what to keep when editing. Raise thinking_level for complex layouts and lower it for speed.

Recommended Settings

• •Infographics and diagrams: output_resolution 2K, thinking_level high, output_format png, aspect_ratio 4:3. Quote each label.
• •Reference fusion / product placement: add references to image_urls, thinking_level high, output_resolution 2K. Address each reference by position.
• •Photo edits: supply one reference, thinking_level medium, output_resolution 2K. State the change and what to keep.
• •Wide banners and panoramas: aspect_ratio 4:1 or 8:1, output_resolution 2K or 4K, thinking_level medium.
• •Current-events visuals: enable web_search to ground on real-time data.

Example prompts to try

Each example below ran end to end on Segmind at the settings shown, and every detail named in the prompt — labels, kept objects, framing — carried through to the output.

• •Legible science infographic (default). Prompt: "A clean educational infographic: a cross-section cutaway of an erupting stratovolcano against a pale grid background. The cutaway reveals the interior with neat leader lines connecting to legible labels reading 'MAGMA CHAMBER', 'CENTRAL VENT', 'SIDE VENT', 'LAVA FLOW', 'ASH CLOUD', and 'ROCK STRATA'. A bold title 'ANATOMY OF A VOLCANO' runs across the top, with a small compass rose and a scale bar in the lower corner. Flat vector illustration style with layered rock colours and a rising ash plume." All six callouts were spelled correctly and placed with leader lines. Tip: keep label text in quotes and use thinking_level high for dense diagrams.
• •Wide panorama without seams. Prompt: "A seamless ultrawide interior panorama looking down the nave of a vaulted Gothic library: rows of carved oak bookshelves and long reading tables recede toward a tall rose window, brass reading lamps glowing, daylight falling from clerestory windows. One continuous scene with no repeated sections." The 4:1 frame held together with no tiling. Tip: pair 4:1 or 8:1 with 2K or 4K and ask for one continuous scene.

Reference-guided edits and fusion

Nano Banana 2.1 accepts up to 14 reference images; refer to each by position (the first reference image, the second reference image).

• •Multi-image fusion (two references). Prompt: "Place the tin wind-up robot from the first reference image and the vintage twin-lens camera from the second on a sunlit oak desk, the robot holding the camera up to its eye. Keep both objects' exact shapes, colours and worn metal textures from the references." Both objects kept their identity from the two separate photos. Tip: use 2K and thinking_level high for clean compositing.
• •Instruction photo-edit (one reference). Prompt: "Replace the pancakes on the plate with a tall stack of waffles topped with fresh blueberries and a dusting of icing sugar, and change the glass of orange juice into an iced coffee. Keep the plate, cutlery, wooden table and background exactly the same." Only the named items changed; the rest of the table stayed put. Tip: spell out what to keep so edits stay local.

Further prompts it is built for: "render a labeled anatomy diagram of a honeybee with callouts", "place this product on a billboard mockup from the reference", "restyle this portrait as a 1950s studio photograph".

Is Nano Banana 2.1 generally available?

Yes, it reached general availability on October 6, 2026 as the successor to Nano Banana 2.

Can it render readable text in images?

Yes — legible text and infographic layout accuracy are its biggest upgrades over earlier models.

How many reference images can I use?

Up to 14, combined for fusion, editing, and character consistency across subjects.

Does it support image editing as well as generation?

Yes, it edits supplied photos from text instructions while leaving the rest of the frame intact.

What output resolutions are available?

1K, 2K, and 4K; there is no 512px tier.

Are results reproducible with a seed?

The upstream Gemini model may ignore seed, so exact reproducibility is not guaranteed.