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把文章当作配方,先对比图片结果,再把最好的静态图转成视频。Quick Answer
- GPT image 2 is stronger when you need a polished, publish-ready illustration with clear text, complete doodle elements, and a strong social-media cover feel.
- Nano-Banana-2 is stronger when you want a looser, more natural hand-drawn look with less polished AI energy.
- In the food advertising test, GPT image 2 produced the stronger commercial hero image, while Nano-Banana-2 produced the more natural and edible-looking food photo.
- These were same-prompt tests using first outputs from each model. The creative illustration set used mixed saved aspect ratios, so it compares style, prompt adherence, text clarity, and practical usability rather than strict same-size composition.
Prompts credit: Sairah (@Sairah_0) on X. All prompts were originally created and shared by Sairah. Used with attribution for research and comparison purposes only.
Key Takeaways
- Use GPT image 2 when the output needs to look polished enough for a cover, prompt example, article hero, or commercial first frame.
- Use Nano-Banana-2 when natural texture, looser drawing, or less staged food realism matters more than maximum visual impact.
- Treat the food advertising case as a 4:3 same-prompt comparison. Treat the creative illustration case as a style and usability comparison because the saved output ratios are mixed.
- Do not use one result as a universal model ranking. Use it as a practical starting point for deciding which model to test first.
Why Same-Prompt Tests Matter
Different AI image generators interpret the same words differently. A prompt that produces a clean, cheerful illustration in one model might look rough or off-tone in another. Testing with identical prompts removes the variable of prompt quality — you're comparing the model's taste, not yours.
For creators, this matters because the "best" image model is not always the model with the most realistic output. Sometimes you need readable text. Sometimes you need a rougher hand-drawn feeling. Sometimes you need a first image that is strong enough to become a Hub article hero, a carousel cover, or the first frame for an image-to-video workflow.
Test Setup
The two Reemo tests below were run on different dates, with one first output saved from each model in each case.
| Test detail | Value |
|---|---|
| Workflow | Text to image |
| Models tested | GPT image 2 and Nano-Banana-2 |
| Runs per model | 1 |
| Image selection | First output from each model |
| Reference image | None |
| Main comparison focus | Food-ad drama, edible realism, creative illustration style, prompt adherence, readable doodle text, and publishability |
The test uses two cases:
| Case | Date tested | Prompt type | Aspect ratio note |
|---|---|---|---|
| Case 1 | June 24, 2026 | Melted cheese burger food advertising prompt | 4:3 outputs |
| Case 2 | June 10, 2026 | Crayon-style creative illustration prompts | Mixed saved aspect ratios |
The creative illustration outputs use mixed saved aspect ratios:
| Image | Saved dimensions | Approximate ratio |
|---|---|---|
| GPT image 2 bumblebee children | 1122 x 1402 | 4:5 portrait |
| Nano-Banana-2 bumblebee children | 1024 x 1024 | 1:1 square |
| GPT image 2 woman portrait | 1122 x 1402 | 4:5 portrait |
| Nano-Banana-2 woman portrait | 896 x 1200 | 3:4 portrait |
Because the creative illustration aspect ratios are mixed, this article does not treat that case as a strict same-size composition benchmark. The useful question is more practical: given the same creative prompt, which model gives a creator a better first result for a specific use case?
Food Advertising Test
The first test uses a commercial food advertising prompt. The goal is not just to make a burger look correct, but to create a still image that could work as a landing-page hero, an ad visual, or the first frame for image-to-video.
Prompt — Melted Cheese Burger
Stream of melted cheese being poured onto a gourmet burger, creating smooth flowing curves and splashes, glossy reflections, high-speed capture, studio lighting, dark elegant background, ultra-premium fast food advertising style.
| GPT image 2 | Nano-Banana-2 |
|---|---|
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Food Advertising Scorecard
| Dimension | GPT image 2 | Nano-Banana-2 | Notes |
|---|---|---|---|
| Prompt adherence | 4.8 | 4.2 | GPT image 2 more closely follows "splashes", "high-speed capture", and "ultra-premium advertising style." Nano-Banana-2 follows the cheese-pour idea, but with less visual force. |
| Composition | 4.7 | 4.1 | GPT image 2 makes the burger larger and more centered, which works better for a cover or hero image. Nano-Banana-2 feels more lifestyle-oriented, with side elements spreading attention. |
| Subject accuracy | 4.5 | 4.6 | GPT image 2 clearly shows the burger and cheese, but the cheese covers more of the subject. Nano-Banana-2 preserves the burger structure more clearly. |
| Texture / style | 4.8 | 4.4 | GPT image 2 creates stronger cheese gloss, fluid motion, and commercial ad texture. Nano-Banana-2 feels more realistic and edible, but less visually explosive. |
| Tiny details | 4.2 | 4.5 | Nano-Banana-2 has more natural table, fries, herb, and burger-layer details. GPT image 2 uses details mainly to support visual impact. |
| Video-readiness as first frame | 4.8 | 4.2 | GPT image 2 has a stronger dynamic starting point for image-to-video. Nano-Banana-2 can work too, but feels more like a food-making shot. |
Food Advertising Takeaway
GPT image 2 is better when the goal is a dramatic commercial advertising still. The cheese stream, splash droplets, dark studio background, and centered hero composition make the image feel like a campaign visual or a video opening frame.
Nano-Banana-2 is better when the goal is realistic food photography. The burger structure is easier to read, the side ingredients feel more natural, and the image looks more edible. The tradeoff is that the overall visual impact is less intense.
In this Reemo same-prompt food advertising test, GPT image 2 delivered a more dramatic commercial advertising still, while Nano-Banana-2 produced a more realistic and edible-looking food photography result.
Creative Illustration Test
The second test uses two crayon-style illustrated portrait prompts. Both prompts were originally created by Sairah (@Sairah_0) on X. They are detailed, playful, and full of doodle elements.
Prompt 1 — Children in Bumblebee Costumes
Crayon-style illustrated portrait of two children wearing bumblebee costumes, laughing and leaning over a wooden ledge. The older child has dark hair with bee antennae and black-and-yellow striped wings; the younger toddler wears a full bee hoodie suit. Surrounding doodles include a cool sun with sunglasses, a flying cartoon bee saying "Bzzz!", a pink heart, smiley face emoji, colorful flowers, stars, and text reading "HA HA!", "LOL!". Childlike crayon texture throughout, white background, bright and playful.
Prompt 2 — Woman Portrait
Crayon-style illustrated portrait of a young woman with long black hair, winking one eye and flashing a peace sign. She wears a soft pink top with rosy blush cheeks. Surrounding doodles include a thought bubble saying "Coffee First!", an iced coffee cup, a cartoon cat, a flower, hearts, stars, a smiley face, and colorful text reading "Good Vibes", "Ha Ha Ha!", and "I ❤️ Nap!". Fun, expressive crayon sketch style, white background, vibrant and cheerful.
Prompt 1 — Bumblebee Children
| GPT Image 2 | Nano Banana 2 |
|---|---|
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Prompt 2 — Woman Portrait
| GPT Image 2 | Nano Banana 2 |
|---|---|
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Creative Illustration Scorecard
| Dimension | GPT image 2 | Nano-Banana-2 | Notes |
|---|---|---|---|
| Prompt adherence | 4.8 | 4.3 | GPT image 2 covers more requested objects, text phrases, and doodle elements. Nano-Banana-2 captures the main idea but simplifies details. |
| Text rendering | 4.8 | 4.4 | GPT image 2 is clearer and more abundant. Nano-Banana-2 keeps several text elements readable, especially in the woman portrait, but with less coverage. |
| Crayon / hand-drawn feel | 4.2 | 4.8 | Nano-Banana-2 feels more naturally hand-drawn. GPT image 2 is cleaner and more polished, but slightly less raw. |
| Character expression | 4.7 | 4.6 | Both produce warm expressions. GPT image 2 is more polished; Nano-Banana-2 is more playful and loose. |
| Composition for publishing | 4.8 | 4.3 | GPT image 2 is stronger for covers, article visuals, and social posts. Nano-Banana-2 is simpler and less visually dense. |
| Creative authenticity | 4.3 | 4.8 | Nano-Banana-2 has less AI-polished energy and feels closer to a handmade illustration. |
| Social / article hero readiness | 4.8 | 4.1 | GPT image 2 is easier to use as a strong hero or social image; Nano-Banana-2 is better when authenticity matters more than impact. |
Strengths and Weaknesses
Prompt 1 — Bumblebee Children
GPT image 2 strengths
- Strong prompt adherence: it includes the two children, bee costumes, sun with sunglasses, flying bee, flowers, stars, hearts, and multiple text elements.
- Text is clear and readable, including "HA HA", "LOL", "Bzzz", and an extra "BEE HAPPY!" phrase.
- The image has strong cover potential for a social post, prompt example, or article hero.
- Facial expressions are warm, polished, and immediately engaging.
GPT image 2 weaknesses
- The faces and lighting feel more polished than a purely childlike crayon drawing.
- The output is very clean, which reduces the raw hand-drawn feeling.
- It adds extra text that was not explicitly requested, which may be useful visually but is still a prompt deviation.
Nano-Banana-2 strengths
- The crayon texture feels more natural, loose, and close to a hand-drawn cartoon.
- The two characters feel stylistically consistent with the doodle environment.
- The result feels less AI-polished and more like a playful illustration.
Nano-Banana-2 weaknesses
- Some requested details are simplified or missing compared with GPT image 2.
- Text is readable, but less abundant and less visually precise.
- The image is calmer and less cover-like, so it has less immediate publishing impact.
Prompt 2 — Woman Portrait
GPT image 2 strengths
- Strong element coverage: coffee bubble, iced coffee, cat, hearts, stars, smiley face, text, wink, peace sign, and pink outfit are all present.
- Text rendering is clear and colorful.
- The composition is rich and visually full, which makes it strong for social graphics and prompt-example articles.
- The character face is polished, friendly, and expressive.
GPT image 2 weaknesses
- The hand and face are a little too refined for a fully raw crayon sketch.
- The image feels more like a finished digital illustration with crayon texture than a spontaneous hand-drawn doodle.
- The overall layout feels more designed than childlike.
Nano-Banana-2 strengths
- The line work has a more natural crayon feel and a simpler hand-drawn composition.
- "Coffee First!", "Good Vibes", "I ❤️ Nap!", and "Ha Ha Ha!" remain surprisingly readable.
- The character looks cohesive with the doodle style.
- The result feels less overproduced and more like a personal illustration.
Nano-Banana-2 weaknesses
- It omits or simplifies some requested surrounding doodle elements.
- The composition is less dense and less dramatic than GPT image 2.
- It is less suitable as a high-impact hero image, though it may be better for authentic hand-drawn style.
Which Should You Use?
Choose GPT image 2 if: You need the doodle elements and text in the image to be accurate. You're making content for social media, children's material, prompt examples, or Hub visuals that need to look clean and immediately usable. You want a first output that is easier to publish with minimal extra selection.
Choose Nano-Banana-2 if: You prefer a more raw, hand-drawn aesthetic. You want something that feels less "AI-generated" and more unique. You're using the image for personal creative projects, looser illustration exploration, or content where a handmade feeling matters more than commercial polish.
| Creator goal | Better starting point |
|---|---|
| Dramatic food advertising hero image | GPT image 2 |
| Image-to-video first frame with strong motion cue | GPT image 2 |
| Natural edible-looking food photography | Nano-Banana-2 |
| Clear doodle text inside the image | GPT image 2 |
| More complete coverage of a detailed prompt | GPT image 2 |
| Social cover or Hub article hero | GPT image 2 |
| More authentic crayon texture | Nano-Banana-2 |
| Less polished, more handmade feeling | Nano-Banana-2 |
| Creative exploration where imperfections are welcome | Nano-Banana-2 |
Recommendation
For commercial visuals, GPT image 2 is the safer first choice when the output needs to be dramatic, centered, polished, and ready for a hero image or video first frame. Nano-Banana-2 is a better fit when the food, object, or scene should feel more natural and less staged.
For crayon-style creative illustration, GPT image 2 is the safer first choice when the output needs to be clear, complete, and publishable. Nano-Banana-2 is the better choice when the goal is a more natural hand-drawn texture, softer imperfections, and a less overproduced creative feel.
In this Reemo same-prompt creative illustration test, GPT image 2 produced cleaner, more complete, and more readable crayon-style images, while Nano-Banana-2 produced a looser and more authentic hand-drawn illustration feel.
Together, the two tests show the same pattern from different angles: GPT image 2 is usually stronger when clarity, completion, and publishing polish matter; Nano-Banana-2 is stronger when natural texture and less polished creative believability matter more.
FAQ
Which AI image generator is better for crayon-style art? Both GPT image 2 and Nano-Banana-2 handle crayon-style prompts well, but they produce different aesthetics. GPT image 2 tends to be cleaner, more complete, and more polished. Nano-Banana-2 is looser, more hand-drawn, and less overproduced. The better choice depends on whether you need publishability or authenticity.
Which model is better for food advertising images? GPT image 2 was stronger for a dramatic melted-cheese burger ad image, especially when the goal was a premium campaign still or an image-to-video first frame. Nano-Banana-2 was stronger for natural food believability because the burger structure and side details looked more edible.
Which model is better for readable text inside illustrations? GPT image 2 was stronger in this test. It produced clearer and more abundant doodle text across both prompts. Nano-Banana-2 also rendered several phrases surprisingly well, especially in the woman portrait, but it was less complete.
Which model feels less AI-generated? Nano-Banana-2. Its crayon texture, simpler composition, and loose line work feel closer to a handmade illustration. GPT image 2 looks cleaner and more controlled, which is helpful for publishing but can feel more digitally produced.
Does the same prompt always produce the same result? No. AI image generators are non-deterministic — even with the same prompt and model, you'll get different outputs each time. This test captures one representative generation per model.
Was this a same-size benchmark? No. The food advertising test used 4:3 outputs, while the creative illustration test used mixed saved aspect ratios. The comparison is most useful for judging style, prompt adherence, text clarity, and practical creator use cases.
Can I use these prompts for my own projects? The prompts were originally created by Sairah (@Sairah_0) on X. You're welcome to use them for personal testing, but please credit the original author if you publish the results.
Methodology and Update Notes
This comparison is based on Reemo internal same-prompt tests. The food advertising test was run on June 24, 2026 with 4:3 outputs and one first output saved from each model. The creative illustration prompts were tested on June 10, 2026 with first outputs saved from each model, but the saved aspect ratios were mixed.
Evaluation focused on prompt adherence, composition, text clarity, visual texture, publishing readiness, and usefulness as a first frame for image-to-video. The scorecards are Reemo editorial assessments of these saved outputs, not a universal benchmark.
Prompt attribution: the two crayon-style prompts were originally shared by Sairah (@Sairah_0) on X and are used here for educational and comparison purposes with attribution.
Last reviewed: June 25, 2026. Added the standard GEO article structure, clarified the aspect-ratio caveat, and separated internal methodology from external prompt attribution.





