Let's build the GPT Tokenizer. When Andrej Karpathy left OpenAI last week a lot of people expressed hope that he would be increasing his output of educational YouTube videos.
Here’s an in-depth 2 hour dive into how tokenizers work and how to build one from scratch, published this morning.
The section towards the end, “revisiting and explaining the quirks of LLM tokenization”, helps explain a number of different LLM weaknesses—inability to reverse strings, confusion over arithmetic and even a note on why YAML can work better than JSON when providing data to LLMs (the same data can be represented in less tokens).
Recent articles
- The Summer of Johann: prompt injections as far as the eye can see - 15th August 2025
- Open weight LLMs exhibit inconsistent performance across providers - 15th August 2025
- LLM 0.27, the annotated release notes: GPT-5 and improved tool calling - 11th August 2025