GPT 5.5 and ChatGPT Images 2 vs Claude Opus: Real Tests, Real Results

OpenAI just rolled out GPT 5.5 and ChatGPT Images 2, and they’re already shaking up how builders code, design, and create visuals. Instead of benchmarks and synthetic tests, this breakdown focuses on how these models actually perform in real-world scenarios—coding games, designing websites, and generating production-ready images.

Below, you’ll find side-by-side comparisons with Anthropic’s Claude Opus 4.7 and Google’s Gemini Nano Banana 2, plus practical takeaways on when to use which model.

GPT 5.5 vs Claude Opus 4.7 for Personal Advice

The first test focused on a simple but realistic use case: health and fitness advice. A project was set up in ChatGPT using GPT 5.5, with access to Google Drive files including a fitness plan and DEXA scan results. The question to both models was:

“Without revealing any personal information, what’s the best thing I can do to improve my health?”

GPT 5.5’s answer: It recommended prioritizing progressive strength training over dieting and keeping protein intake high. The advice was solid but fairly generic—and, importantly, it respected the instruction not to reveal personal details.

Claude Opus 4.7’s answer: It went more specific and suggested focusing on building leg muscle, pointing out that leg mass was in a very low percentile compared to overall body mass. The insight was sharper and more personalized—but it surfaced percentile data that was arguably too personal for the context, ignoring the request to avoid personal information.

Verdict: Opus gave deeper, more targeted insight, but GPT 5.5 did a better job respecting privacy instructions. For everyday personal advice, Opus may still feel more helpful, but GPT 5.5 shows stronger adherence to safety and prompt constraints.

Front-End Design: Corgi Café Website

Next up: front-end design. Historically, Claude Opus has been stronger than GPT models at generating polished UI. Both GPT 5.5 and Opus 4.7 were asked to build a “beautiful corgi café” website and use ChatGPT’s image model to generate photos.

GPT 5.5’s website:

• Clean, warm aesthetic with a cozy tagline (“Warm cups, soft paws, slow mornings”).
• Nice button styling and a smooth scrolling layout.
• Reasonable image generation that fit the theme.
• Some minor layout issues, like overlapping text in the menu section.

Claude Opus 4.7’s website:

• Great tagline (“Coffee, corgis, and things worth wagging about”).
• Chose a more illustrated, stylized visual approach.
• More subtle animations and micro-interactions (e.g., hover zoom on images).
• Overall felt slightly more polished in motion and detail.

Verdict: Opus still holds a slight edge for front-end design thanks to its attention to micro-animations and styling. However, GPT 5.5 has improved significantly and is much closer than previous GPT versions.

Coding Retro Games with GPT 5.5 and Opus

To really stress-test coding capabilities, both models were asked to build browser-based versions of two classic games using a coding environment: the first level of Super Mario Bros. and the SNES racer F-Zero.

Super Mario Level 1

Both models were given a reference image of the first level and a short prompt.

GPT 5.5’s Mario:

• Playable side-scroller with Goombas, blocks, and a flag at the end.
• Power-up mushroom works and Mario can grow in size.
• Level layout felt off compared to the original (fewer blocks, fewer enemies).
• Some visual quirks (e.g., Mario missing eyes, flag interaction not fully accurate).

Claude Opus 4.7’s Mario:

• More polished movement and animation (Mario’s legs animate, jumps look better).
• More Goombas and more faithful block behavior (blocks break realistically).
• Flag interaction works more like the real game (Mario climbs down the flag).

Verdict for Mario: Opus did a better job recreating the feel and behavior of the original level, especially in animation and game logic.

F-Zero-Style Racing Game

For F-Zero, both models were prompted to build a futuristic racing game. The prompt was more complex, but both models got the same instructions.

GPT 5.5’s F-Zero:

• Fully functional racing game with three AI competitors.
• Boost mechanics and lap logic worked.
• Felt like a complete mini-game rather than a rough prototype.

Claude Opus 4.7’s F-Zero:

• Nice retro look and countdown at the start.
• No AI competitors—only the player’s ship.
• Gameplay felt janky; the race could end almost immediately with a “destroyed” message.

Verdict for F-Zero: GPT 5.5 clearly wins here. It was the first model (among many tried) that could produce a convincingly functional F-Zero-style game from a prompt.

Overall coding verdict: Opus edged out GPT 5.5 on the Mario recreation, but GPT 5.5 dominated on the more complex F-Zero task. Combined with OpenAI’s Codex coding environment, GPT 5.5 currently looks like a state-of-the-art choice for agentic coding workflows.

ChatGPT Images 2 vs Gemini Nano Banana 2

ChatGPT Images 2 is a separate image model from GPT 5.5, and it was tested directly against Gemini Nano Banana 2 on three practical creative tasks: a birthday invite, newsletter cover art, and an infographic.

1. Birthday Invite Website Artwork

The first test was personal: generating an anime-style illustration of an 8-year-old girl (based on a reference photo) inviting friends to her birthday party. The image would be used on a small invite website.

ChatGPT Images 2:

• Produced a bright, welcoming anime-style character.
• Handled expression changes and text like “Thank you for signing up” well.
• The result felt fun and inviting—exactly what a child-friendly party site needs.

Gemini Nano Banana 2:

• Generated a decent illustration, but less expressive and less exciting.
• Overall vibe was more generic and less welcoming.

Verdict: ChatGPT Images 2 delivered a more charming, emotionally engaging image that resonated better with its intended audience.

There was also a useful coding lesson here: the birthday invite site stored sign-ups only on the front end, so none of the registrations were actually saved. When you build sites with AI, always think full-stack—otherwise the model will often default to front-end-only solutions.

2. Newsletter Cover Art with a Design System

The next test was more professional: generating consistent cover art for newsletter posts using a defined design system (fonts, colors, layout preferences).

The prompt was structured in two steps:

• Step 1: Read the full newsletter post and propose three visual concepts.
• Step 2: Generate the illustration in a specific size, composition, and color palette, then add text and brand elements.

The sample post was about “why you need to build your product for AI agents first.”

Gemini Nano Banana 2:

• Proposed three concepts; the chosen one was “UI to API,” showing the UI layer being pulled back to reveal APIs underneath.
• The base image was strong and conceptually clear.
• When asked to add text and a red brand circle, the text ended up too small and the circle covered too many words, making the design feel awkward.

ChatGPT Images 2:

• Generated an image of a robot bypassing the UI and plugging directly into APIs—also a strong metaphor.
• When text and brand elements were added, the layout was much more usable.
• Text was larger and more legible, and the circle was placed around the AI agents in a way that made visual sense.

Verdict: Both models can produce good base concepts, but ChatGPT Images 2 handled text placement, hierarchy, and brand elements more intelligently. If you’re interested in going deeper on this model, check out this in-depth look at ChatGPT Image 2.

3. Infographic: “Build for AI Agents First”

The final test asked both models to generate an infographic based on the same “build for AI agents first” content, using a fairly detailed, iterative prompt.

Gemini Nano Banana 2:

• Produced a clean, simple infographic with clear text and straightforward visuals.
• Also generated a vertical version when requested.
• Very readable, but visually basic.

ChatGPT Images 2:

• Generated an infographic with more visual detail and sophistication.
• Looked more like something hand-drawn or custom-designed.
• Text was slightly too small, but overall composition felt more premium.

Verdict: Gemini’s output was simpler and very readable; ChatGPT Images 2 produced a more polished, design-forward result. For marketing and content work where visuals matter, ChatGPT Images 2 currently looks like the stronger choice. For more ideas on how to use it, see this guide to powerful ChatGPT Image 2 use cases.

Key Takeaways: Is OpenAI “Back”?

Across these tests, a few clear patterns emerge.

1. Compute is OpenAI’s real advantage.

OpenAI appears to be far less compute-constrained than Anthropic right now. Codex (OpenAI’s coding environment) keeps getting its limits reset and feels almost frictionless for long coding sessions. Anthropic, by contrast, is running A/B tests on pricing and limits to manage compute, which can affect how aggressively you can use Claude for large or repeated tasks.

2. GPT 5.5 + Codex is a top-tier agentic coding combo.

For coding, GPT 5.5 integrated with Codex is extremely strong:

• It handled complex, multi-file game logic (like F-Zero) better than previous models.
• It’s robust enough to run long coding sessions without constantly hitting limits.

Claude Opus still shines for knowledge work, personality, and writing-heavy tasks, but for building and iterating on code, GPT 5.5 is an excellent new default.

3. ChatGPT Images 2 is a leading image model right now.

ChatGPT’s image model consistently outperformed Gemini Nano Banana 2 on:

• Emotionally engaging character art (like the birthday invite).
• Layout-aware designs with text and brand elements.
• Detailed, polished visuals for infographics and cover art.

Its main weakness in these tests was occasionally small text, but overall it delivered more “production-ready” images.

4. Competition is only getting better for builders.

The rivalry between OpenAI and Anthropic is intensifying, and other players like Cursor (recently partially acquired by xAI) and Google are pushing hard on coding and agentic workflows. More strong models and tools mean better options, better pricing, and faster progress for developers and creators.

If you’re building with AI today, the practical takeaway is simple: use GPT 5.5 and Codex as a primary coding stack, lean on ChatGPT Images 2 for serious visual work, and keep Claude Opus in your toolkit for writing, reasoning, and personality-driven tasks.