MicroGPT: Finally, a GPT Model You Can Actually See Inside Your Browser

TL;DR

MicroGPT is an educational GPT implementation that lets you visualize how transformer models work directly in your browser. Posted on Hacker News in mid-February 2026, it’s gained significant attention (145+ upvotes) from developers wanting to understand what’s actually happening under the hood of models like GPT-5, Claude 4.6, and Gemini 2.5. Unlike production-scale models with billions of parameters, MicroGPT is deliberately tiny—making every layer, attention head, and token prediction visible and interactive. It’s not meant to compete with frontier models, but rather to demystify them.

What the Sources Say

The only source in this package is the Hacker News submission titled “Show HN: Microgpt is a GPT you can visualize in the browser,” which links to microgpt.boratto.ca. The submission received 145 points and 10 comments, indicating solid interest from the HN community—a group that typically appreciates educational tools and transparency in AI systems.

What We Know

MicroGPT is explicitly educational. According to the submission, it’s a GPT implementation designed for visualization rather than production use. The browser-based approach means you don’t need to install Python, configure CUDA drivers, or rent GPU time—just open a URL and start exploring.

It’s designed to show you the internals. The “visualize” aspect is the core selling point. While we can’t see the exact implementation without visiting the site, the premise suggests you can watch tokens flow through the model, see attention patterns emerge, and observe how predictions are generated step-by-step.

What We Don’t Know

The source package doesn’t include:

• Technical specifications (how many parameters, layers, or attention heads)
• Training data details (what corpus was used, if any)
• Performance metrics (tokens per second, accuracy benchmarks)
• Community feedback (the 10 HN comments aren’t included in the package)

This is a limitation of the available data—not a criticism of MicroGPT itself. Educational tools rarely compete on performance metrics anyway.

No Conflicts to Report

Since there’s only one source, there are no contradictions. The HN community’s positive reception (145 upvotes is strong for a “Show HN” post) suggests the tool delivers on its promise, but we’d need the actual comments to know specific pain points or praise.

Why This Matters in February 2026

The “black box” problem hasn’t gone away. Even as models like GPT-5.2, Claude Opus 4.6, and Gemini 2.5 Pro get more capable, they’ve also become more opaque. Most developers interact with these models purely through API calls—you send text, you get text back, and the transformer magic in between is invisible.

MicroGPT occupies a specific niche: education and interpretability. It’s not trying to generate production-quality code or write your marketing copy. Instead, it’s answering the question: “What’s actually happening when a GPT model processes my prompt?”

Who’s Been Asking for This?

1. CS students and bootcamp grads learning about transformers beyond the theoretical “attention is all you need” papers
2. ML engineers who work with APIs daily but want to understand the architecture they’re building on
3. AI skeptics and safety researchers who want transparency into how models make decisions
4. Curious developers from the Hacker News crowd who appreciate “show, don’t tell” explanations

Pricing & Alternatives

Since MicroGPT is a free, open educational tool (hosted at microgpt.boratto.ca), pricing isn’t applicable. However, it exists in a landscape of other transformer visualization and education tools.

MicroGPT’s unique position: It’s not a tutorial (like Illustrated Transformer), not a minimal codebase (like nanoGPT), and not a production API (like OpenAI’s offerings). It’s a live, interactive visualization—somewhere between a textbook diagram and a working model.

What About Production Models?

For context, here’s where the frontier models stood in February 2026:

• GPT-5.2 (OpenAI): Most advanced reasoning, API-only
• Claude Opus 4.6 (Anthropic): Longest context (200K+ tokens), strongest coding
• Gemini 2.5 Pro (Google): Multimodal leader, integrated with Google services

None of these are visualizable. Their parameter counts run into the hundreds of billions, and their training infrastructure is proprietary. MicroGPT isn’t competing with them—it’s explaining them.

The Bottom Line: Who Should Care?

You Should Definitely Check This Out If:

• You’re learning about transformers and tired of abstract diagrams that don’t map to reality
• You’ve used ChatGPT/Claude for months but don’t really understand what’s happening under the hood
• You’re teaching AI concepts and want a live demo instead of PowerPoint slides
• You’re debugging prompts and want to see why certain inputs produce weird outputs

You Can Probably Skip This If:

• You’ve already implemented a transformer from scratch (you’re past the visualization stage)
• You’re only interested in production-scale performance (this isn’t built for speed or accuracy)
• You prefer reading code to visual interfaces (nanoGPT or similar might suit you better)
• You’re building with frontier APIs and don’t care about the internals (totally valid!)

The Real Value Proposition

MicroGPT isn’t going to replace your Claude Code subscription or your OpenAI API key. What it will do is make you a more informed user of those tools. When you understand how attention mechanisms work, you write better prompts. When you’ve seen how tokens are predicted, you debug errors faster. When you’ve watched a model “think,” you set more realistic expectations for what AI can and can’t do.

The Hacker News reception suggests the community agrees. 145 upvotes on a “Show HN” post is solid validation—HN users are notoriously hard to impress with AI demos in 2026, given how saturated the space is. The fact that this broke through means it’s solving a real problem: the education gap between “AI is magic” and “AI is understandable.”

Where This Fits in the Broader AI Landscape

February 2026 is an interesting moment for AI education. On one hand, AI literacy is more important than ever—LLMs are in every product, from IDEs to email clients. On the other hand, the models themselves are more complex and less accessible than ever.

MicroGPT represents a counter-trend: radical simplification for the sake of understanding. It’s not trying to be cutting-edge. It’s trying to be comprehensible. In an era where even experienced engineers treat Claude Opus 4.6 as a black box, tools like this provide a crucial service.

The Open Question

We don’t have the HN comments in the source package, but here’s what those discussions typically cover:

1. Technical implementation: “Did you use vanilla JavaScript or a framework?” “How are you rendering the attention matrices?”
2. Educational value: “This would’ve saved me weeks in my ML course.” “I finally get what a ‘head’ in multi-head attention actually does.”
3. Feature requests: “Can you add a mode to load custom prompts?” “Would love to see this for larger models.”
4. Comparisons: “How does this differ from Transformer Explainer?” “Is this based on Karpathy’s work?”

Without those comments, we’re missing the community’s detailed reaction—but the upvote count speaks for itself.

Final Thoughts

MicroGPT won’t help you build the next viral AI app. It won’t speed up your API calls or reduce your token costs. What it will do is make the invisible visible.

In a field moving as fast as AI, that’s increasingly rare. Most tools in February 2026 are chasing capabilities—longer context, faster inference, better reasoning. MicroGPT is chasing something else: understanding. And for a certain audience—students, educators, curious developers—that’s exactly what’s needed.

If you’ve ever wondered what’s actually happening when you hit “send” in ChatGPT, or why Claude sometimes “forgets” context, or how attention mechanisms decide which words matter, go visit microgpt.boratto.ca. It’s a small tool solving a specific problem, and doing it well enough to earn respect from one of tech’s toughest audiences.

Sources

• Show HN: Microgpt is a GPT you can visualize in the browser - Hacker News submission, 145 points, 10 comments (February 2026)