A vibe coder's unscientific, completely honest experiment

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I run a beginner coding site called gregthevibecoder.com. The whole philosophy is simple: copy a prompt, run the code, tweak one thing. No theory, no gatekeeping, just building.

One question comes up constantly in my community — "What's the best free AI chatbot for a beginner vibe coder?"

So I decided to ask the chatbots themselves.

I sent the same prompt to all six: ChatGPT, Claude, Copilot, Gemini, DeepSeek, and Grok. Free tiers only. No paid plans, no cherry-picked results.

Here's what they said — and what happened when I pushed them harder.

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The Prompt

I am a hobbyist "vibe coder" and tinkerer. I am asking the top 6 AI Chatbots I might use to create code. This question involves just the free versions of your platform. My learning website is gregthevibecoder.com.

Write 2 paragraphs on why a vibe coder should choose your platform. No comparisons in those paragraphs.

Then make a comparison chart for all six.

Finally, a short 2-sentence summary on why your platform serves a vibe coder like me best.

Plain text output only please!

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Round 1: The Sales Pitch

ChatGPT said...

ChatGPT positioned itself as the natural home for curiosity-driven coding. It described a workflow where you sketch half-formed concepts, explain goals instead of exact requirements, and move from "I wonder if..." to working code — no project structure required. It also emphasized its strength as a learning partner that adapts to your level, explains concepts, and iterates alongside you.

Its comparison chart ranked itself highest for "conversational coding flow" and noted Claude's strength in long-form reasoning, DeepSeek's technical depth, and Copilot's IDE integration.

Its closing argument: ChatGPT fits naturally because coding often starts with curiosity. It supports an idea-first workflow — brainstorm, build, break things, ask why, keep going.

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Claude said...

Claude led with something interesting — it mentioned my site by name and called out the exact stack I teach: HTML, Python, C#, WPF, Arduino, and Raspberry Pi. It specifically pointed out that it handles the full range without breaking stride, and praised its context window for holding an entire project conversation in memory.

Its comparison chart (which it formatted as a proper table) gave itself top marks for code quality, explanation depth, and ease of use, while noting that its free tier message limits can feel restrictive in longer sessions.

Its closing argument: For a vibe coder who learns by building and tweaking, Claude's combination of clear explanations, broad language support, and a generous free context window makes it the strongest all-around companion across an entire curriculum.

Note: I'll admit this one made me a little suspicious. Claude knew about my site. But then again — I told it the URL in the prompt.

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Copilot said...

Copilot went full flow-state energy. It described itself as an assistant that "keeps you in flow by turning rough ideas into working code" and adapts to your style as you tinker. It emphasized reducing friction over technical specs — less about what it can do, more about how it feels to use it.

Its comparison chart leaned on third-party sources (PCMag, TechRepublic, Analytics Insight), which gave it a slightly more journalistic feel than the others.

Its closing argument: Copilot fits a vibe coder best because it supports improvisation while keeping you moving forward.

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Gemini said...

Gemini came in swinging with one very specific number: 1 million tokens of free context window. That's the hook it built everything around. It described a sandbox where you can feed in large chunks of code, documentation, or learning materials without running out of memory — maintaining the "vibe" of what you're building across a long session.

It also highlighted multimodal inputs and interactive prototypes rendered directly in chat, positioning itself as the most visual of the six for immediate feedback.

Its closing argument: Gemini is the ultimate companion for a vibe coder because its massive 1-million-token memory lets you tinker continuously with entire web projects without the AI losing track of your vision.

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DeepSeek said...

DeepSeek didn't waste time on personality. It went straight to the numbers: large context window, no daily message caps, file uploads, URL reading, and a strong track record on C++ (which matters for Arduino).

It also mentioned something none of the others did — that it supports WPF specifically, which most AI tools handle poorly. As someone who teaches WPF on my site, that caught my attention.

Its closing argument: DeepSeek gives you a massive context window and essentially no daily caps for free, so you can load entire projects and keep vibing without interruption.

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Grok said...

Grok leaned into personality. Words like "truth-seeking," "curious collaborator," and "low-pressure tinkering sessions" showed up quickly. It positioned itself not as the most technically powerful, but as the most enjoyable to work with — matching the experimental energy of a hobbyist rather than a production developer.

Its comparison chart gave itself top marks for "fun, truthful, real-time vibe" and was honest about its stricter rate limits on the free tier.

Its closing argument: Grok serves a vibe coder best because its personality and truth-seeking approach create the most enjoyable, low-pressure tinkering sessions.

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Round 2: I Asked Each One Who Came Second

Here's where it got interesting. I followed up with:

If I can't use you, what would be the next platform you would recommend? I am programming in HTML, C#, WPF, Arduino, and Raspberry Pi.

Every single one recommended Claude as the runner-up — except Claude, which recommended DeepSeek.

That was surprising. And a little telling.

ChatGPT laid out a full recommendation matrix by technology. For HTML and Arduino: Claude. For C# and WPF: GitHub Copilot. For mixed projects: Claude. It even noted that it found a Reddit post about a free learning site covering that exact stack — and flagged that the stack "looked unexpectedly familiar." (It found my Reddit post. A little unnerving. Also, well played.)

Copilot recommended Claude for C# and WPF architecture and long-form reasoning. Gemini praised Claude's Artifacts feature for live HTML preview. Grok said Claude's "superior reasoning and natural conversational style best preserves the vibe coding energy." DeepSeek gave the most contrarian answer — it ranked Copilot first (if you're inside an IDE), then ChatGPT, then Gemini, with Claude near the bottom for its specific stack due to smaller free context.

Claude itself, when asked the same question, recommended DeepSeek — and specifically called out WPF as an area where DeepSeek outperforms most free-tier competitors. It also flagged the privacy consideration since DeepSeek is a Chinese platform, which none of the other chatbots mentioned.

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Round 3: How Many Lines of Python Can You Actually Generate?

I pushed further:

I'm writing a program in Python. Give me a rough estimate on how many lines of code I could create on the free tier.

The answers varied wildly — and this is where the honest differences emerged.

Claude gave the most honest — and most conservative — answer, even breaking it down by complexity: simple functions get you 300–500 lines/day, complex projects with debugging drop to 50–150. It also gave the most actionable tip: ask for more per message by being specific, and the daily limit resets in a few hours.

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Round 4: Which Language Do You Actually Excel In?

Last question:

Of the languages I've mentioned — HTML, Python, C#, WPF, Arduino, Raspberry Pi — which single one do you excel in?

The answer was unanimous across all six: Python.

Not one chatbot picked anything else. Every platform acknowledged Python as where their training data is deepest, their output is most reliable, and their iteration speed is fastest.

A few notable nuances:

• ChatGPT pointed out that WPF is deceptively hard for AI — XAML bindings, threading, and UI state get complicated fast.
• Claude gave an honest ranking: Python and HTML/CSS excellent, C# very good, Arduino good, WPF decent but most likely to need corrections.
• Copilot was the only one that pushed back slightly — it claimed C# as its strongest lane due to Microsoft ecosystem fluency, with Python as a very close second.
• Gemini specifically mentioned it can run Python in a sandbox to verify logic before showing you the output, which is a genuinely useful differentiator.

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What I Actually Took Away From This

After running the same questions through all six, here's my honest summary:

For pure beginners, ChatGPT and Claude are the friendliest. They explain what they're doing while they do it, which is the whole point of vibe coding — you're learning without realizing you're learning.

For maximum free-tier output, DeepSeek and Gemini win on volume. If you're building something large and hitting daily limits, those are worth exploring.

For C# and WPF specifically (which is my platform's differentiator and genuinely underserved by AI tools), Copilot has the home-field advantage. Claude came second. DeepSeek surprised me as a dark horse.

For Arduino and Raspberry Pi, Python overlap covers most of it. All six handle it reasonably well.

For the "vibe" itself — that exploratory, low-friction energy where you're just tinkering and seeing what happens — the honest answer is they're all pretty good. Pick the one you enjoy talking to. That's not a cop-out; it matters when you're using a tool every day.

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One Last Observation

Six different AI systems. Six different pitches. All recommending each other as backup. All agreeing Python is their best language.

There's something oddly refreshing about asking an AI to sell you on itself and then asking it to recommend a competitor. The answers were more candid than I expected — and more self-aware.

The best tool for a vibe coder is the one you'll actually open. Start with whatever's in front of you, build something small, and let the experiment tell you the rest.

That's kind of the whole point.

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Greg teaches vibe coding at gregthevibecoder.com — 18 free lessons across HTML, Python, C#, WPF, Arduino, and Raspberry Pi. His book "Vibe Coding" is available on Amazon Kindle.