[{"data":1,"prerenderedAt":20},["ShallowReactive",2],{"explain-image2-vs-nanobanana-architecture-real-test":3},{"id":4,"title":5,"slug":6,"summary":7,"cover_image":8,"content":9,"tags":10,"status":16,"sort_order":17,"created_at":18,"updated_at":19},15,"GPT-Image-2 vs Nano Banana: An Architect Real-World Head-to-Head Test","image2-vs-nanobanana-architecture-real-test","Systematic comparison of GPT-Image-2 and Nano Banana Pro across 11 architectural design scenarios.","\u002Fimage\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-00.webp","\u003Ch2>Introduction\u003C\u002Fh2>\n\u003Cp>As soon as GPT-Image-2 launched, I ran a systematic head-to-head comparison with the Nano Banana series — using architectural design as the test arena: renderings, presentation boards, analysis diagrams, storyboards, style transfer — tested one by one.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Bottom line:\u003C\u002Fstrong> GPT-Image-2 is \u003Cstrong>NOT\u003C\u002Fstrong> a replacement for Nano Banana Pro\u002F2 — it's a complementary tool worth adding to your toolbox. When Banana is unstable, GPT steps in. For simple tasks, it's more than adequate.\u003C\u002Fp>\n\u003Cul>\n\u003Cli>\u003Cstrong>Use GPT first for:\u003C\u002Fstrong> Presentation boards, posters, report materials, Chinese text annotations, creative concepts, brand content production.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Use Banana first for:\u003C\u002Fstrong> Aerial views, large-scale planning, storyboard grids, style transfer, complex spatial consistency tasks.\u003C\u002Fli>\n\u003C\u002Ful>\n\n\u003Ch2>8 Key Comparison Insights\u003C\u002Fh2>\n\n\u003Ch3>01 — Presentation Boards & Posters: GPT is Currently the Best\u003C\u002Fh3>\n\u003Cp>This is GPT-Image-2's standout scenario, bar none. Layout logic is clear, section partitioning is reasonable, and the text-image relationship shows genuine design sensibility — not the chaotic AI pile-up you'd expect. Same prompt, Banana outputs \u003Cstrong>\"usable\"\u003C\u002Fstrong>, GPT outputs \u003Cstrong>\"beautiful.\"\u003C\u002Fstrong>\u003C\u002Fp>\n\n\u003Cp>\u003Cstrong>Case 1: Plant Species Identification Board\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>\u003Cem>Prompt: Create a design board identifying 8 major plant species in this photo, providing clear labels and descriptions for each, including leaf shape, color, height, and typical habitat.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-00.webp\" alt=\"Case 1 - Input\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Input image\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-01.webp\" alt=\"Case 1 - GPT Output 1\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-02.webp\" alt=\"Case 1 - GPT Output 2\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-03.webp\" alt=\"Case 1 - Nano Pro Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Nano Pro output\u003C\u002Fp>\n\n\u003Cp>\u003Cstrong>Case 2: Xiangmi Park Urban Design Board\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>\u003Cem>Prompt: Using the uploaded satellite image of Shenzhen Xiangmi Park, transform the highlighted area into a futuristic Chinese-themed amusement park with roller coasters, rides, and themed architectural elements. Generate a comprehensive urban design board including master plan, cross-section details, eye-level renderings (including night views), detailed planting schemes, massing studies, and urban planning analysis diagrams for traffic circulation, functional zoning, and public space usage. All annotations bilingual Chinese-English.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-04.webp\" alt=\"Case 2 - Input\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Input image\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-05.webp\" alt=\"Case 2 - GPT Output 1\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-06.webp\" alt=\"Case 2 - GPT Output 2\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-07.webp\" alt=\"Case 2 - Nano Pro Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Nano Pro output\u003C\u002Fp>\n\n\u003Ch3>02 — Chinese Text Generation: GPT is Currently the Most Accurate\u003C\u002Fh3>\n\u003Cp>This directly matters for architects in China. Banana has persistent garbled text issues with Chinese characters. GPT-Image-2 shows significant improvement — annotations are accurate, Chinese characters are largely error-free, even in densely packed text on complex boards. For text-heavy visual tasks, GPT is the more reliable choice.\u003C\u002Fp>\n\n\u003Cp>\u003Cstrong>Case 3: Interior Space Plan with Details\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>\u003Cem>Prompt: Based on this interior space, generate a floor plan design description with storyboarded detail views showing specific soft furnishing and cabinetry details.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-08.webp\" alt=\"Case 3 - Input\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Input image\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-09.webp\" alt=\"Case 3 - GPT Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-10.webp\" alt=\"Case 3 - Nano Pro Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Nano Pro output\u003C\u002Fp>\n\n\u003Ch3>03 — Stronger Semantic Understanding: More Complex Prompts = Better Results\u003C\u002Fh3>\n\u003Cp>GPT-Image-2 has high fidelity to prompt execution. The more precise and complex your instructions, the more it follows your intent. For experienced architects who can write long prompts, GPT has a higher ceiling.\u003C\u002Fp>\n\n\u003Cp>\u003Cstrong>Case 4: Building Section with Interior Details\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>\u003Cem>Prompt: Based on this building, generate a realistic-style cross-section with interior decoration and perspective, maintaining structural rationality while showing internal functional zones and circulation routes. Remove unnecessary textures and surroundings.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-11.webp\" alt=\"Case 4 - Input\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Input image\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-12.webp\" alt=\"Case 4 - GPT Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-13.webp\" alt=\"Case 4 - Nano Pro Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Nano Pro output\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Evaluation:\u003C\u002Fstrong> Banana's output was clean with accurate floor-level function labels. GPT went beyond the brief — automatically adding small analysis diagrams and function icons. When relevant descriptions were removed from the prompt, these extras disappeared too, confirming GPT's proactive semantic understanding.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>GPT's interpretive expansion is an advantage, but requires precise prompt control to avoid generating unwanted content.\u003C\u002Fstrong>\u003C\u002Fp>\n\n\u003Ch3>04 — Complex Architectural Spaces: Banana is Still the Go-To\u003C\u002Fh3>\n\u003Cp>This is GPT's most obvious weakness. Aerial views, large-scale spatial understanding, storyboard grids — whenever the task involves complex architectural spatial logic, GPT falls apart. For complex spatial tasks, Banana remains the primary choice.\u003C\u002Fp>\n\n\u003Cp>\u003Cstrong>Case 5: FPV Drone 9-Grid Storyboard\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>\u003Cem>Prompt: Generate a 9-grid storyboard of an FPV drone racing around this building at high speed — descending through clouds, diving to the base, 360° orbit, flying through the building, exiting from the top, and ascending to altitude.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-14.webp\" alt=\"Case 5 - Input\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Input image\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-15.webp\" alt=\"Case 5 - GPT Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-16.webp\" alt=\"Case 5 - Nano Pro Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Nano Pro output\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Evaluation:\u003C\u002Fstrong> Banana's 9 outputs showed strong spatial consistency with logical camera progression — basically usable as video material. GPT's 9 outputs had inconsistent proportions, broken details, and chaotic spatial relationships across all quality tiers.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Storyboard tasks are currently GPT's clear weakness — not recommended for this scenario.\u003C\u002Fstrong>\u003C\u002Fp>\n\n\u003Cp>\u003Cstrong>Case 6: Multi-Angle 9-Grid Storyboard\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>\u003Cem>Prompt: Generate 9 different angle storyboards including: ground-level looking up, street perspective, distant wide shot, telephoto detail, lobby interior, balcony, interior-through-glass city view, roof garden, and aerial overview.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-17.webp\" alt=\"Case 6 - Input\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Input image\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-18.webp\" alt=\"Case 6 - GPT Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-19.webp\" alt=\"Case 6 - Nano Pro Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Nano Pro output\u003C\u002Fp>\n\n\u003Ch3>05 — Bold Color Style: Not Suitable for All Projects\u003C\u002Fh3>\n\u003Cp>GPT's output tends toward oversaturated, darker tones — a \u003Cstrong>\"trying too hard\"\u003C\u002Fstrong> visual tendency with dramatic lighting and strong color contrast. This is an advantage for creative\u002Fatmospheric tasks but problematic for color-accurate modifications requiring faithful original tones. Architects report: fine for early concept exploration, but a headache at the color-precise stage.\u003C\u002Fp>\n\n\u003Cp>\u003Cstrong>Case 7: Style Transfer Rendering\u003C\u002Fstrong>\u003C\u002Fp>\n\u003Cp>\u003Cem>Prompt: Use the rendering style and lighting atmosphere of Image 2 to render Image 1 in high-quality photorealism. Preserve all geometry and spatial layout from Image 1. Transfer color, material, lighting, lens quality and premium urban atmosphere from Image 2.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-20.webp\" alt=\"Case 7 - Input 1\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Input Image 1\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-21.webp\" alt=\"Case 7 - Input 2\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Input Image 2\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-22.webp\" alt=\"Case 7 - GPT Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-23.webp\" alt=\"Case 7 - Nano Pro Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Nano Pro output\u003C\u002Fp>\n\n\u003Ch3>06 — Unstable Output Ratios, Occasional Low Quality\u003C\u002Fh3>\n\u003Cp>GPT-Image-2 has a unique quality tiering mechanism — low, medium, high quality levels. Higher quality means cleaner output with fewer AI artifacts. But this parameter is currently only controllable via API; web users get randomly assigned quality tiers, sometimes producing jittery lines and smeared details. Output aspect ratios also occasionally deviate from originals. Using the API with specified quality tiers gives a much more stable experience.\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-24.webp\" alt=\"Quality Comparison\" \u002F>\u003C\u002Ffigure>\n\n\u003Ch3>07 — Faster Speed, but No Price Advantage\u003C\u002Fh3>\n\u003Cp>GPT-Image-2 generates faster than Banana in testing — a plus. But pricing offers no surprises — roughly on par with Nano Banana Pro at ¥1-2 per image for high-quality, large-format output. Compared to Nano Banana 2's ¥0.30 per 1K image after price cuts, GPT isn't competitive on cost. For batch-rendering teams, GPT currently isn't the cost-effective option.\u003C\u002Fp>\n\n\u003Ch3>08 — When Banana is Unstable, GPT Can Save the Day\u003C\u002Fh3>\n\u003Cp>A recent discovery: Banana has been experiencing instability — same prompt works during the day but fails at night, or repeated attempts can't produce satisfactory results. In these cases, GPT-Image-2 can serve as a temporary stand-in, especially for simple single-image tasks and presentation board needs. Running both tools simultaneously as mutual backups is currently the most stable workflow configuration.\u003C\u002Fp>\n\n\u003Ch2>Additional Test Cases\u003C\u002Fh2>\n\n\u003Ch3>Case 8: Execute Text Instructions from Image\u003C\u002Fh3>\n\u003Cp>\u003Cem>Prompt: Generate the work described by the text instructions in this image, and remove the text from the image.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-25.webp\" alt=\"Case 8 - Input\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Input image\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-26.webp\" alt=\"Case 8 - GPT Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-27.webp\" alt=\"Case 8 - Nano Pro Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Nano Pro output\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Evaluation:\u003C\u002Fstrong> Banana executed all instructions precisely with correct proportions. GPT completed most modifications but had a typical issue: the original image contained a person, and GPT couldn't place the figure at the correct scale — either deleting or severely distorting proportions.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>For multi-instruction, spatially complex editing tasks, Banana is more stable.\u003C\u002Fstrong>\u003C\u002Fp>\n\n\u003Ch3>Case 9: Dark-Background Technical Section Board\u003C\u002Fh3>\n\u003Cp>\u003Cem>Prompt: Based on this building, generate a photorealistic dark-background vertical section analysis board including functional module analysis, structural analysis, lighting design analysis, construction layer analysis, with the original image as the main visual occupying ~1\u002F4. All text in English.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-28.webp\" alt=\"Case 9 - Input\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Input image\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-29.webp\" alt=\"Case 9 - GPT Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-30.webp\" alt=\"Case 9 - Nano Pro Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Nano Pro output\u003C\u002Fp>\n\n\u003Ch3>Case 10: Construction Process Analysis\u003C\u002Fh3>\n\u003Cp>\u003Cem>Prompt: Generate a construction analysis for this building, detailing each step from foundation to main structure, facade construction, and finally soft furnishing and landscaping.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-31.webp\" alt=\"Case 10 - Input\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Input image\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-32.webp\" alt=\"Case 10 - GPT Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-33.webp\" alt=\"Case 10 - Nano Pro Output\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Nano Pro output\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Evaluation:\u003C\u002Fstrong> Banana produced 5-6 clear evolution steps. GPT delivered nearly 20 steps — from empty lot, excavation, construction to completion, with illustrated details at every stage. Information volume far exceeded expectations.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>GPT's expansion capability is both a strength and a risk — for formal presentations, explicitly limit step counts in the prompt, otherwise the output becomes overly dense.\u003C\u002Fstrong>\u003C\u002Fp>\n\n\u003Ch3>Case 11: Logo-to-Headquarters Design\u003C\u002Fh3>\n\u003Cp>\u003Cem>Prompt: Generate an official architectural headquarters design matching the气质 and style of this logo. The logo name is AIRI Lab.\u003C\u002Fem>\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-34.webp\" alt=\"Case 11 - Input\" \u002F>\u003C\u002Ffigure>\n\u003Cp>Input image\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-35.webp\" alt=\"Case 11 - GPT Building\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output (building headquarters)\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-36.webp\" alt=\"Case 11 - GPT Website UI\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output (official website UI design for the headquarters)\u003C\u002Fp>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-37.webp\" alt=\"Case 11 - GPT Tour Guide\" \u002F>\u003C\u002Ffigure>\n\u003Cp>GPT-Image-2 output (visitor guide image for the headquarters)\u003C\u002Fp>\n\u003Cp>\u003Cstrong>Evaluation:\u003C\u002Fstrong> The most surprising test of the entire session. GPT not only accurately understood the logo's design language and generated architectural renderings with water features and industrial-style interiors, but also produced a complete, well-typeset website UI design with legible text.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>This kind of purely creative task is completely beyond Banana's capabilities. GPT has a unique advantage here, worth exploring for brand content creation and concept development.\u003C\u002Fstrong>\u003C\u002Fp>\n\n\u003Ch2>Bonus: AI4ELAB Test\u003C\u002Fh2>\n\u003Cfigure>\u003Cimg src=\"\u002Fdata\u002Fimages\u002Fprompt-explain-image2-vs-nanobanana-architecture-real-test-38.webp\" alt=\"AI4ELAB Test\" \u002F>\u003C\u002Ffigure>\n\u003Cp>One image from AI4ELAB testing. More in the next article.\u003C\u002Fp>\n",[11,12,13,14,15],"Image2","NanoBanana","architecture","comparison","benchmark",1,100,"2026-05-21T07:03:03.000Z","2026-05-21T07:52:43.000Z",1781516709036]