The AI image generation wars have reached a fever pitch, and if you've been paying attention, you know Google has been on an absolute tear lately. Their Nano Banana Pro has been setting the standard for months, leaving competitors scrambling to catch up.
Last night, OpenAI entered the ring with their answer: GPT Image 1.5. Not the rumored 2.0 we'd all been expecting—just 1.5. That version number alone tells a story.
I spent eight hours putting both models through their paces, running identical prompts through GPT Image 1.5 and Nano Banana Pro. The results? More nuanced than you might expect. While the headlines might declare a clear winner, the reality is far more interesting for anyone actually using these tools.
Let me walk you through what I found.
The Backstory
Remember March 26th this year? That was when OpenAI first unveiled GPT-4o's image generation capabilities—GPT Image 1.0. That same day, Google launched Gemini 2.5 Pro. Looking back now, Gemini 2.5 Pro turned out to be truly groundbreaking.
But on that particular day? Everyone on X (formerly Twitter) and in every Discord server I'm in was talking exclusively about GPT-4o. We joked that "1.5 Pro got buried by Sora, and 2.5 Pro got buried by 4o."
Fast forward six months, and wow, how the tables have turned. Now it's OpenAI getting absolutely demolished by Google on a daily basis.
So this time around, instead of the rumored GPT Image 2.0, they went with version 1.5—just like Google did with their Nano Banana Pro upgrade. Call me cynical, but it feels like they're hedging their bets, afraid of another embarrassing comparison. According to TechCrunch's coverage of OpenAI's code red response, the company accelerated this release after internal pressure to compete with Google's recent advances. Six months ago, OpenAI was riding high. Who could've predicted this outcome?
The New ChatGPT Image Interface
Along with the model update, ChatGPT rolled out a completely redesigned image interface. When you open it up, you're greeted by this soft pink background.
I've got to hand it to OpenAI—they clearly put more effort into the consumer experience than Google does. They've separated out style presets and quick commands into their own dedicated sections. For instance, if I select the "sugar cookie" style preset, a popup appears asking me to either choose from recent images I've sent to ChatGPT or upload a new one.
Here's where it gets weird: the system literally takes my image and the default prompt, then sends it to ChatGPT as a regular conversation message. Honestly? The UX feels clunky. You're bouncing between different interfaces, and it gets confusing fast.
That said, the generation speed has definitely improved. According to OpenAI's official announcement, the new model offers up to 4x faster image generation speeds. I clocked it at roughly 40 seconds to 1 minute on ChatGPT. After that wait, you get your sugar cookie-style image. There's also a plush toy style option, among others.
Beyond style transfers, there are practical quick-action presets like "create professional product photos" or "generate professional headshots." The interaction flow is identical—click, upload image, select options. The results are honestly pretty solid.
You can even transform photos into famous paintings using templates. Though I noticed the facial details lose some of those characteristic brushstroke textures and end up looking overly smooth.
After spending all night testing the core model capabilities, I found some genuinely interesting highlights. For this review, I wanted to directly pit GPT Image 1.5 against Nano Banana Pro so you can clearly see their respective strengths, limitations, and which one comes out on top.
Information Accuracy
Text accuracy is absolutely the number one concern for multimodal AI image generation right now, so let's start there.
Prompt: Generate photo of a desktop 2026 February calendar, below it a standard 7-column grid (Sun Mon Tue Wed Thu Fri Sat), filled with dates 1–28, requiring grid alignment, clear numbers, and no other text except the title and dates.
GPT Image 1.5
Nano Banana Pro
Right out of the gate, GPT stumbled hard. I specifically requested dates only up to 28. Nano Banana Pro executed this perfectly—every single number was correct. But GPT? It kept going past 28, adding 29 and 30. That's a complete failure.
According to Google's Nano Banana Pro documentation, one of the model's key improvements is "Enhanced World Knowledge" which allows for more accurate text rendering in images like infographics and diagrams—something clearly demonstrated in this test.
Photorealistic Quality
Now let's examine how realistic their direct photo generation looks and which produces more authentic results.
Prompt: Portrait of a young woman with fair, pale skin: natural flush on skin, nose and cheeks without freckles. Short ash-brown bob with center part and layers, a few loose strands falling beside her face; light brown eyes, curled lashes, full glossy pink lips. Expression playful and mischievous: winking one eye, tongue out, cute and cheeky. She's casually seated on a bar stool, wearing a black tank top with an open or draped light blue/white/black plaid flannel shirt over it, denim mini skirt with a small black belt. Left hand hanging naturally, holding a lit cigarette. Scene is a dimly lit outdoor or semi-outdoor bar/pub/nightclub: stone or metal-textured round table and bar stools; on the table is a glass filled with a drink, and a glass pitcher. Background blurred, faintly showing seated people and nighttime ambient lighting. Shot from a high angle (looking down at subject), strong direct flash, sharp shadows cast behind the figure, skin bright and slightly overexposed. Overall style: casual snapshot, Y2K aesthetic, street style, grunge, flash photography. 3:4 aspect ratio, authentic film texture, slight grain, shallow depth of field.
GPT Image 1.5
Nano Banana Pro
Both systems clearly have strong semantic understanding—nearly every element I specified showed up. In terms of quality, GPT's images tend to look more AI-generated and overly glossy, while Banana Pro delivers more authentic realism.
Prompt: Generate a photorealistic candid shot: an elderly sailor standing on a small fishing boat organizing nets, with a dog sitting quietly beside him. Require visible authentic skin texture (wrinkles, pores, sun damage), worn clothing with salt stains; natural seaside daylight. Camera specs: 50mm, medium close-up, eye level, shallow depth of field, slight film grain; unposed, unretouched; 3:4 aspect ratio.
GPT Image 1.5
Nano Banana Pro
These two are basically tied, though GPT consistently pushes higher saturation and contrast, while Banana Pro maintains a more natural, everyday look.
Prompt: Generate a photorealistic candid shot: backstage dressing room after a performance. Scene: A row of vanity mirrors with light bulbs, desktop scattered with makeup brushes, hair clips, water bottles, tissues; light sources are mirror bulb lights (warm) + overhead room lighting (neutral), realistic mixed lighting. Subjects: At least 6 performers/crew members: Foreground: one person seated getting makeup done, makeup artist beside them touching up (hand movements clearly visible); Midground: two people adjusting costumes and earpieces; Mirror reflections must show consistent reality (matching number of people, poses, positions—no extra or missing people magically appearing). Photography specs: 50mm, f/1.8, 1/160s, ISO 2500; medium close-up; shallow depth of field.
GPT Image 1.5
Nano Banana Pro
GPT still has that same issue—contrast and saturation running a bit hot, giving the overall color palette a slightly artificial AI feel. Personally, I prefer Banana Pro's texture. It's more natural.
Precise Editing
One of the most practical features in modern AI image generation is the ability to make targeted edits without regenerating the entire image. This is where things get interesting between these two models.
I tested both systems with a common scenario: editing specific elements while keeping the rest of the composition intact. For example, I started with a portrait and requested changes like "make the background a sunset beach" or "change the shirt color to navy blue while keeping everything else the same."
GPT Image 1.5 handled these requests with mixed results. When I asked for simple color changes, it performed admirably—swapping a red dress to blue while maintaining the exact pose and lighting. However, when I requested more complex edits like changing backgrounds or adding objects, the model sometimes reinterpreted the entire scene, giving me something aesthetically pleasing but not quite what I asked for.
Banana Pro, on the other hand, demonstrated superior precision in this department. The model seemed to better understand the concept of "minimal intervention." When I asked it to change just the background, it literally changed only the background, preserving even subtle details like hair wisps and lighting reflections that matched the new environment. This level of precision editing is crucial for professional workflows where consistency matters.
For localized edits—like removing a person from a group photo or changing a single object—Banana Pro consistently outperformed GPT. It understood spatial relationships better and maintained coherence across the edited regions. GPT occasionally introduced artifacts or strange blending issues at the boundaries of edited areas.
This isn't to say GPT is bad at editing; it's actually quite capable for casual users. But if you're a designer or content creator who needs surgical precision in your image modifications, Banana Pro currently holds the edge.
World Knowledge
Here's where things get really fascinating—testing how well these AI image models understand real-world concepts, physics, and logical relationships. This goes beyond just rendering pretty pictures; it's about whether the AI truly "gets" how the world works.
Prompt: Create a square image containing the following: a hand with seven fingers, a wall clock showing the time 8:22, and a wine glass filled with red wine.
This is where things got really interesting. GPT Image 1.5 actually got the time right! Well, almost—the hour hand should be positioned slightly higher, but the minute hand is accurate. As for the seven fingers? It rendered six instead.
Banana Pro completely dropped the ball here, failing on both the hand and the clock.
But let me dig deeper into world knowledge testing. I ran several other experiments to see how these models handle real-world accuracy:
Brand logos and typography: I asked both to generate images featuring recognizable brand products. GPT struggled significantly with accurate logo reproduction—often creating "inspired by" versions rather than accurate representations. Banana Pro showed similar challenges but occasionally got closer to realistic branding, though neither should be relied upon for brand-accurate work.
Physical laws and shadows: When I requested scenes with specific lighting conditions—like "a ball casting a shadow at 2 PM in summer"—Banana Pro demonstrated better understanding of how light and shadows actually work. GPT sometimes produced shadows that didn't match the light source direction or time of day.
Cultural and geographical accuracy: I tested prompts like "traditional Japanese tea ceremony setup" and "authentic Italian piazza architecture." Both models showed decent cultural awareness, but Banana Pro included more accurate contextual details—proper utensil placement in the tea ceremony, correct architectural proportions in the piazza.
Historical accuracy: For prompts involving historical periods or events, neither model is perfect, but GPT occasionally introduced anachronistic elements. When I asked for a "1920s speakeasy interior," it sometimes included modern design elements.
So when it comes to world knowledge, I'd call this pretty much a draw with situational advantages. GPT excels at time-telling and certain logical sequences, while Banana Pro shows stronger understanding of physical laws and spatial relationships. Each has its wins and losses, and your choice should depend on what type of accuracy matters most for your specific use case.
Final Thoughts
I spent an entire night putting GPT Image 1.5 through its paces. It's not bad by any means, but I can't say it's exceptional either. Compared to Nano Banana Pro, it still falls short in several areas.
And here's what really gets me: OpenAI spent six months since their March release just to produce this. Meanwhile, Google? They went from Gemini 2.5's image generation to Imagen 3 (Banana) in three months, then evolved Banana into Banana Pro in another three months. As The Verge reported on OpenAI's flagship image model, the competitive pressure has never been higher. That company's evolution speed is genuinely terrifying.
Google truly deserves its crown as the current king of AI.
This time around, it's OpenAI's turn to play catch-up.
Author's AI Image Toolbox
- Current King (Overall): Google Nano Banana Pro
- Main Contender: OpenAI GPT Image 1.5
- Newcomer to Watch (For Exploring Specific Features): z-image.ai - Focusing on deeper stylistic editing and logical consistency.
