Make Readable Text in Nano Banana 2 Images

Text in AI images used to mean smeared hieroglyphs. Nano Banana 2 is better—but only if you treat copy like a layout spec, not an afterthought.

Rule 1: double quotes everywhere

Any characters that must appear literally go in "double quotes":

A minimalist poster, cream background, headline "SUMMER DROP" in bold black grotesk, subline "JUNE 12" smaller beneath

Unquoted words become scene description fuel and mutate.

Rule 2: fewer words beat paragraphs

Headlines under ~25 characters survive best. Split long copy across multiple quoted spans with size hints (“large”, “small caption”).

Open Nano Banana Studio

In Gemini, follow up: Change only the headline to "LAST CALL" in red. Nano Banana’s conversational edit preserves composition better than a from-scratch roll.

Multilingual signage

Name the script explicitly: Traditional Chinese characters "夏季特卖" on a storefront awning. Mixing languages in one quoted block without labels increases glyph errors.

Quick QA checklist

Each text element quoted separately?
Font style described (sans, serif, neon tube)?
Background contrast mentioned?
Proof at 1K before 4K export?

When to stop fighting the model

Paragraphs, fine print, and curved warp text still belong in Figma or Photoshop. Generate clean background + short hero type, composite the rest.

Prerequisites and setup

You need a modern browser with hardware acceleration enabled to render the preview canvas smoothly without lag. Ensure your MidassAI account is active on the Pro tier, as the Nano Banana 2 model requires higher compute credits than standard diffusion runs. We are assuming version 2.1 of the model, which includes the latest glyph correction patches released last month. Older versions struggle significantly with Latin character consistency.

Have a vector editor like Illustrator or a raster tool like Photoshop ready for immediate post-processing. Even with perfect generation, kerning often needs manual adjustment before final export for client work. Keep your workspace organized with separate layers for background assets and typography elements to streamline this hybrid workflow. This setup prevents bottlenecks when iterating on multiple design variations simultaneously.

Extended prompt workflow

Define the canvas ratio explicitly before typing copy. Set aspect ratio to 4:5 for social media or 16:9 for web banners. This dictates how the model wraps lines and prevents awkward breaks mid-word.
Construct the prompt using a strict "subject + context + text" hierarchy. Example: Product shot of soda can, condensation, studio lighting, label text "FIZZY". Place the text instruction at the very end of the prompt string for maximum attention.
Apply negative prompting to remove common artifacts immediately. Use --no blurry text, misspelled, extra letters, gibberish to clean up edges around the glyph boundaries.
Set guidance scale between 7 and 9 depending on complexity. Higher values enforce prompt adherence strictly but reduce creative lighting variations. Lower values allow more style drift.
Generate four variations initially to test consistency. Pick the image with the clearest letterforms, not necessarily the best lighting or composition. Legibility is the priority here.
Upscale only the selected region containing the text using the inpaint tool. This saves compute credits and maintains sharpness where it matters most without regenerating the entire scene.

Common mistakes

Overloading the prompt string: Putting too many words in one quote block causes the model to drop characters or merge them. Fix: Split long sentences into separate visual elements or reduce the copy to essential keywords only.
Ignoring lighting direction on surfaces: Text painted on 3D objects needs to match the scene light source or it looks floating. Fix: Add "shadow cast by text" and "reflective surface" to the prompt description to ground the typography.
Skipping the zoom check during review: Text looks fine at thumbnail size but breaks into noise at 100% view. Fix: Always zoom to 100% pixel view before approving any generation batch for client delivery or final export.

Try this in MidassAI

Ready to test these techniques without installing local dependencies? Open the studio dashboard and select the Nano model from the model dropdown menu. Paste your structured prompt into the input box and adjust the guidance sliders based on the workflow outlined above. The interface allows real-time tweaking of text parameters before committing credits. You can access the tool directly here to start your first legible generation: https://www.midassai.com/studio/nano/