Three of Andrej Karpathy's open-source repositories, nanoGPT, nanochat, and micrograd, have accumulated more than 120,000 GitHub stars combined, making him one of the most-followed technical educators in machine learning. Two years to the day after founding Eureka Labs, that body of work has brought him to Anthropic's pretraining team.
The Nano* Philosophy: Teaching AI by Removing Everything Extra
The nano* series rests on a single conviction: the fastest route to genuine understanding is a complete, working implementation that fits on one screen. Karpathy introduced micrograd in 2020 as a compact, scalar-valued autograd engine: a minimal backpropagation implementation in pure Python with no external dependencies. The repository now has more than 16,000 GitHub stars and is widely cited as the most approachable entry point to gradient-based learning in the field.
nanoGPT, released in January 2023, applied the same reduction to transformer language models. Its README describes the project as "the simplest, fastest repository for training/finetuning medium-sized GPTs." It accumulated more than 60,000 GitHub stars and became one of the most-forked machine-learning repositories on the platform, enabling a generation of practitioners to learn the transformer architecture through direct implementation rather than reading papers alone.
nanochat arrived in October 2025, extending the lineage to a full ChatGPT-class system. By January 2026, the repository documented a training run that reproduced a GPT-2-class conversational model for roughly $73 on a single eight-GPU H100 node in three hours, putting full-stack AI model training within reach of individual researchers on a limited budget. nanochat surpassed 43,000 GitHub stars. In February 2026, Karpathy published microgpt on his personal blog: a single Python script of 200 lines, no dependencies, that both trains and runs inference on a GPT from scratch. He described it on his blog as "the culmination of multiple projects (micrograd, makemore, nanogpt, etc.) and a decade-long obsession to simplify LLMs to their bare essentials."
Eureka Labs: Two Years of Scaling the Thesis
On July 16, 2024, exactly two years before today, Karpathy announced Eureka Labs on X, describing it as "a new kind of school that is AI native." The company's thesis was that post-2022 generative AI made it viable to build AI tutors capable of scaling a single domain expert's teaching capacity to an unlimited number of learners, at a quality level that prior ed-tech could not match.
