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title: "Comment by Kartik N V J K on \"Is the most expensive AI the smartest? 23 LLMs, capability vs API price (Oct 2026)\" | Hashnode"
description: "Pricing in the tokenizer gap, where Claude counts about 30% more tokens than GPT for the same text, is the adjustment I check first. I size max-token limits per"
url: "https://hashnode.com/posts/is-the-most-expensive-ai-the-smartest-23-llms-capability-vs-api-price-oct-2026/6ac24b6242884481ab590d08/comment/6ac54d0fbeb26fbf24748304"
---

[Discussion](https://hashnode.com/posts/is-the-most-expensive-ai-the-smartest-23-llms-capability-vs-api-price-oct-2026/6ac24b6242884481ab590d08)

Comment [Is the most expensive AI the smartest? 23 LLMs, capability vs API price (Oct 2026)](https://hashnode.com/posts/is-the-most-expensive-ai-the-smartest-23-llms-capability-vs-api-price-oct-2026/6ac24b6242884481ab590d08)

[Kartik N V J K](https://hashnode.com/@kartik-nvj)

[Oct 6](https://hashnode.com/posts/is-the-most-expensive-ai-the-smartest-23-llms-capability-vs-api-price-oct-2026/6ac24b6242884481ab590d08/comment/6ac54d0fbeb26fbf24748304)

Pricing in the tokenizer gap, where Claude counts about 30% more tokens than GPT for the same text, is the adjustment I check first. I size max-token limits per provider, since a limit tuned for one tokenizer cuts another's JSON reply mid-object. Does your counter run each provider's own tokenizer?

[Jaehyun Cho](https://hashnode.com/@jonhisking)

[Oct 7](https://hashnode.com/posts/is-the-most-expensive-ai-the-smartest-23-llms-capability-vs-api-price-oct-2026/6ac24b6242884481ab590d08/comment/6ac54d0fbeb26fbf24748304#reply-6ac5c6a1719e534d86014489)

Good point on max\_tokens. A limit tuned on one tokenizer can cut another provider's JSON reply mid-object.

To answer your question: OpenAI counts are exact. The o200k\_base tokenizer runs in the browser via js-tiktoken. Claude and Gemini are estimates, since their tokenizers can't run client-side. The counter takes the o200k count and applies a per-family ratio: 1.30 for Claude models since 4.7, 1.05 for Haiku 4.5 and 0.95 for Gemini. For exact Claude numbers, Anthropic's count\_tokens endpoint is the reliable route.

The 30% is an average for English text and shifts with language and content, so I'd still leave some headroom on max\_tokens.