The Same TypeScript Costs 73% More on Claude Than on GPT
Summary
The article examines how tokenizer differences across frontier AI models drive real-world costs. It shows that price per token is not the full story because different tokenizers produce different token counts for the same code, leading to substantial cost differences for coding workloads. It provides a methodology for measuring token counts and offers practical guidance for developers to compare costs across providers based on actual tokens used rather than sticker prices.