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More AI insights from our eval notes
Strong reasoning image model; best known for “contact sheet prompting” (generate a single 6–9 frame grid image from a shot-list prompt, tested up to ~12 frames) and then extract frames. Works well for people/humanoids and close-up/detail when given a reference image; more error-prone for cars/products (frame count/layout drift). Can struggle with exact logos/text—expect iteration for client-critical labels. Recommended workflow: generate the grid at ~2k–4k, redo only the bad frame(s) instead of the whole sheet, extract frames as 1:1 first to preserve detail, then optionally expand (e.g., generative fill) to 9:16 or 16:9; expanding during extraction increased hallucination risk in testing. Rough cost mentioned: ~$0.15 per generation; contact sheets can be cheaper than generating many standalone images (frame extraction adds additional generations).
Nano Banana Pro is Google's most advanced image generation model, powered by Gemini 3. It excels at tasks requiring reasoning and world knowledge: generating accurate infographics, rendering legible stylized text (posters, diagrams, menus), maintaining character consistency across complex scenes, and producing code visualizations. The model can accept up to 14 reference images for composition, making it exceptional for storyboarding and visual narratives. Key improvements over Nano Banana include 4K output, dramatically better text rendering, grounding with Google Search for real-time data, and fine-grained editing controls (camera angles, lighting, depth of field, color grading).
Every Glif test Nano Banana Pro Image Generator has run, straight from our eval suite. Open a test to see how every other model handled the same prompt, or browse the whole suite.
Every output above was scored by gpt-5.5 against the capabilities each test is designed to probe.
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Run Nano Banana Pro Image Generator and every other model on Glif from one chat. One account, one balance, no API keys to wire up.