How LLMs Work – Interactive visual guide based on Karpathy's lecture
All content is based on Andrej Karpathy's "Intro to Large Language Models" lecture (youtube.com/watch?v=7xTGNNLPyMI). I downloaded the transcript and used Claude Code to generate the entire interactive site from it — single HTML file. I find it useful to revisit this content time to time.
How LLMs Work – Interactive visual guide based on Karpathy's lecture launched on April 24, 2026 with 245 votes, #106 of 21,248 launches that month and more than 99% of that year's launches.
In plain words
This is an interactive visual guide explaining how large language models work, based on Andrej Karpathy's "Intro to Large Language Models" lecture. The creator extracted the lecture transcript and used Claude Code to generate an entire interactive website as a single HTML file. It's designed for developers and anyone wanting to understand LLM fundamentals through visual, revisitable content based on established educational material.
written from the facts on this page · September 2026
From the sources
A complete walkthrough of how large language models like ChatGPT are built — from raw internet text to a conversational assistant. Based on Andrej Karpathy's technical deep dive. Representative figures from frontier models circa 2024 — exact numbers shift with every release. The scale is the point, not the precision. The first step is collecting an enormous amount of text. Organizations like Common Crawl have been crawling the web since 2007 — indexing 2.7 billion pages by 2024. This raw data is then filtered into a high-quality dataset like FineWeb . The goal: large quantity of high quality , diverse documents. After aggressive filtering, you end up with about 44 terabytes — roughly 10…from ynarwal.github.io
Does a similar job
all alternatives →- VIVisual intuitive explanations of LLM concepts (LLM University)2023 · ▲303
Hi HN, We've just published a lot of original, visual, and intuitive explanations of concepts to introduce people to large language models. It's available for free with no sign-up needed and it includes text articles, some video explanations, and code examples/notebooks as well. And we're available to answer your questions in a dedicated Discord channel. You can find it here: https://llm.university/ Having written https://jalammar.github.io/illustrated-transformer/, I've been thinking about these topics and how best to communicate them for half a…
I used Claude Code to discover connections between 100 booksJan 2026 · trails.pieterma.es · ▲524I think LLMs are overused to summarise and underused to help us read deeper. I built a system for Claude Code to browse 100 non-fiction books and find interesting connections between them. I started out with a pipeline in stages, chaining together LLM calls to build up a context of the library. I was mainly getting back the insight that I was baking into the prompts, and the results weren't particularly surprising. On a whim, I gave CC access to my debug CLI tools and found that it wiped the floor with that approach. It gave actually interesting results and required very little orchestration…
I built a tiny LLM to demystify how language models workApr 2026 · github.com · ▲915Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.
A Karpathy-style LLM wiki your agents maintain (Markdown and Git)Apr 2026 · github.com · ▲260I shipped a wiki layer for AI agents that uses markdown + git as the source of truth, with a bleve (BM25) + SQLite index on top. No vector or graph db yet. It runs locally in ~/.wuphf/wiki/ and you can git clone it out if you want to take your knowledge with you. The shape is the one Karpathy has been circling for a while: an LLM-native knowledge substrate that agents both read from and write into, so context compounds across sessions rather than getting re-pasted every morning. Most implementations of that idea land on Postgres, pgvector, Neo4j, Kafka, and a dashboard. I…
2000 Large Language Models (LLM) Prompts2023 · miguelanticonam.gumroad.com · ▲106Unlock your knowledge with 2000 LLM prompts
More dev tools this month
the category →
open-source IDE for thoughtful software design. Contribute to devdotfast/whiteboard development by creating an account on GitHub.
Dev tools · 28d ago · github.com
Contribute to reladraw/reladraw development by creating an account on GitHub.
Dev tools · 26d ago · github.com
OpenBot▲362Grok Bot alternative: free, local, open-source, multiplayer
Dev tools · 23d ago · openbot.run
Talanoa▲346Hi HN, I’m a fullstack developer, and honestly, I’ve lost count of how many side projects I’ve worked on over the years. But one idea kept coming back to me: a different kind of email client. It first came to me in 2014: “What if we could handle emails more like conversations?” Every year, I’d revisit this concept in my “Build Notes.” Ten years later, no one had built exactly what I had in mind — so I finally decided to do it myself. That’s how Talanoa was born. I wanted something focused on people, not timelines. I was tired of marking messages as unread just to remember to reply later, or…
Dev tools · 21d ago · talanoa.email
CoreSpeed▲332One MCP for everything your agents need: apps, memory, tools
Dev tools · 28d ago · corespeed.io
Source: Show HN post ↗
Launched alongside, April 2026
the whole month →
- AG
Thought the resources for GPU arch were lacking, so here we are
Life & fun · Apr 2026 · jaso1024.com
Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.
AI · Apr 2026 · github.com
I made a laptop stand out of solid concrete, in the style of brutalist architecture, with themes of urbex and urban decay
Life & fun · Apr 2026 · sam-burns.com
With social media and now AI, its important to keep the indie web alive. There are many people who write frequently. Blogosphere tries to highlight them by fetching the recent posts from personal blogs across many categories. There are two versions: Minimal (HN-inspired, fast, static): https://text.blogosphere.app/ Non-minimal: https://blogosphere.app/ If you don't find your blog (or your favorite ones), please add them. I will review and approve it.
AI · Apr 2026 · text.blogosphere.app