nanochat

In plain words

Nanochat is an open-source implementation of a ChatGPT-like language model that runs on a single GPU. It provides a complete stack for tokenization, pretraining, finetuning, evaluation, and inference, along with a web interface. Designed for developers, nanochat uses minimal dependencies and clean, hackable code to make large language model training and deployment accessible without requiring distributed infrastructure.

written from the facts on this page · September 2026

From the sources

nanochat is a full-stack implementation of an LLM like ChatGPT in a single, clean, minimal, hackable, dependency-lite codebase. Run tokenization, pretraining, finetuning, evaluation, inference, and web UI on a single 8XH100 node.

The best ChatGPT that $100 can buy. Contribute to karpathy/nanochat development by creating an account on GitHub.

nanochat is the simplest experimental harness for training LLMs. It is designed to run on a single GPU node, the code is minimal/hackable, and it covers all major LLM stages including tokenization, pretraining, finetuning, evaluation, and inference. For example, you can train your own GPT-2 capability LLM (which cost ~$43,000 to train in 2019) for only $48 (~2 hours of 8XH100 GPU node) and then talk to it over a simple CLI. On a spot instance, the total cost can be closer to ~$15. More generally, nanochat is configured out of the box to train an entire miniseries of compute-optimal models by setting one single complexity dial: --depth , the number of layers in the GPT transformer model…from github.com

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