Which AI Codes the Best Webpage?

When it comes to AI, one of the biggest mistakes people make is assuming every chatbot performs equally across every task.

They don’t.

In a previous comparison, we looked at how different chatbots handle content creation. This time, we’re testing something more technical: coding a branded contact webpage.

The goal?
Use the exact same prompt across four different systems and compare the outputs.

The result reveals an important lesson: choosing the right chatbot for the task matters.

The Standardized Coding Prompt

To keep the test fair, every chatbot received the same instructions:

• Code a contact webpage for a digital marketing agency website.
• Use attached brand colors.
• Reference a screenshot of the website to inherit style.
• No additional copy provided.

This is what’s often called “vibe coding” — giving high-level direction and letting the AI infer structure, styling, and layout.

No heavy prompting. No over-engineering. Just a standardized task.

The chatbots tested:

• Claude
• Gemini
• Perplexity
• ChatGPT

Let’s break down how each performed.

Claude: Strong Visual Initiative with Minimal Instructions

Claude stood out immediately for one reason:

It was the only system that provided a live preview of the webpage.

That’s a significant usability advantage. Instead of copying code into an HTML viewer, you can immediately see what you’re working with.

What Claude Did Well

• Created a visually structured contact page
• Included a contact form
• Added service sections without being asked
• Implemented hover effects on buttons
• Applied subtle shadow effects
• Demonstrated design initiative

Even without explicit copy instructions, Claude filled in placeholder messaging and created a more complete page experience.

That initiative matters. It reduces iteration time.

Where Claude Shines

Claude performs especially well when:

• Instructions are light
• Design interpretation is required
• Aesthetic cohesion matters
• You want something functional quickly

For “quick vibe coding,” Claude required the least hand-holding.

Gemini: Functional but Minimal

Gemini produced code that technically worked, but it lacked initiative.

Observations

• Basic structure present
• Some hover effects included
• Font selection slightly off-brand
• Minimal content generation
• Less visual richness

It followed instructions but did not expand beyond them.

In practical terms:
It created a form — but not much else.

For fast prototyping, it felt underdeveloped compared to the others.

Perplexity: Surprisingly Strategic Output

Perplexity was not originally thought of as a strong coding assistant — it’s more known for research.

However, its output was surprisingly robust.

What Perplexity Did Well

• Created a navigation bar (one of only two systems to do so)
• Built a structured form
• Included helpful hint text in form fields
• Added service references
• Integrated practical elements like budget fields
• Included hover interactions

It demonstrated more real-world thinking about how a contact page functions.

This is particularly interesting because:
Perplexity often excels at synthesis and applied context.

It seems to understand not just code structure, but website logic.

ChatGPT: Strong Navigation, Weak Body Execution

ChatGPT produced a large amount of code — more verbose than others.

Strengths

• Clean navigation bar
• Good hover effects in header
• Structurally sound code

Weaknesses

• Minimal page content below navigation
• Lacked form visualization
• Less complete user experience
• Required more explicit instruction

ChatGPT performs very well when heavily instructed.

But in a light-instruction scenario, it did not take initiative to fully flesh out the page.

With detailed direction, it likely would improve significantly.

Key Takeaways: Choosing the Right Chatbot for Coding

This comparison reinforces a critical lesson:

Not all chatbots are optimized for the same tasks.

Here’s how they stack up for webpage coding:

• Best for Quick, Aesthetic Vibe Coding: Claude

• Strong Research-Informed Structural Thinking: Perplexity

• Works Well with Detailed Instructions: ChatGPT

• Functional but Less Creative Expansion: Gemini

If your workflow involves rapid prototyping of landing pages, lead magnets, or embedded tools, tool selection matters.

Why This Matters for Marketing Teams

AI is now regularly used for:

• Coding landing pages
• Creating interactive calculators
• Generating HTML email templates
• Building microsites
• Producing gated asset pages

If you choose the wrong system:

• You’ll spend more time iterating
• You’ll over-correct structural gaps
• You’ll manually add missing components

If you choose the right system:

• You reduce friction
• You prototype faster
• You refine instead of rebuild

The Bigger Strategic Lesson

The mistake isn’t using AI.

The mistake is assuming AI tools are interchangeable.

They aren’t.

Each has:

• Different design interpretation tendencies
• Different levels of initiative
• Different verbosity styles
• Different structural logic

When you start cross-referencing tools for specific tasks — content creation, coding, research, strategy synthesis — you move from casual AI use to strategic AI leverage.

Final Verdict

If you’re vibe coding webpages with minimal direction:

Claude currently produces the strongest HTML outputs with the least instruction.

Perplexity deserves more credit than expected.

ChatGPT performs best when you provide structured, detailed direction.

Gemini needs stronger prompting to compete.

In the era of AI-assisted development, success isn’t just about prompting well.

It’s about choosing the right chatbot for the job.