LLM Timeline
An interactive visualization of the evolution of LLM's
LLM Timeline launched on April 10, 2025 with 7 votes.
What it does
An interactive visualization of the evolution of Large Language Models from the Transformer architecture in 2017 to the present.
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AI Timeline – 171 LLMs from Transformer (2017) to GPT-5.3 (2026)Feb 2026 · llm-timeline.com · ▲174Interactive timeline of every major Large Language Model. Filterable by open/closed source, searchable, 54 organizations tracked.
LLM Attention Visualization4d ago · ishamf.dev · ▲172I often need to convert times between time zones, so I built this tool to convert between them quickly and efficiently. 1. Add the cities you want to convert between (this is saved in the browser). 2. Drag on the map until the time on the source city is the time you want. 3. Look at the time at the other city. It's even more helpful to use on a phone since it doesn't require typing to convert between time zones or look up the time in another city (assuming you already added the cities you care about). If you need to convert a time far in the future, you can input the date and time in the…
- 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…
- IGInteractive Graph by LLM (GPT-4o)2024 · columns.ai · ▲45
- HLHow LLMs Work – Interactive visual guide based on Karpathy's lectureApr 2026 · ynarwal.github.io · ▲245
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.
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Hi everyone, I built PyXL — a hardware processor that executes a custom assembly generated from Python programs, without using a traditional interpreter or virtual machine. It compiles Python -> CPython Bytecode -> Instruction set designed for direct hardware execution. I’m sharing an early benchmark: a GPIO test where PyXL achieves a 480ns round-trip toggle — compared to 14-25 micro seconds on a MicroPython Pyboard - even though PyXL runs at a lower clock (100MHz vs. 168MHz). The design is stack-based, fully pipelined, and preserves Python's dynamic typing without static type restrictions.…
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