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Hidden costs in AI deployment: Why Claude models may be 20-30% more expensive than GPT in enterprise settings
It is a well-known fact that different model families can use different tokenizers. However, there has been limited analysis on how the process of “tokenization” itself varies across these tokenizers. Do all tokenizers result in the same number of tokens for a given input text? If not, how different are the generated tokens? How significant […]
Despite lower input token rates of the Anthropic model, we observed that the total costs of running experiments (on a given set of fixed prompts) with GPT-4o is much cheaper when compared to Claude Sonnet-3.5. The ability to proactively estimate token counts (without invoking the actual model API) and budget costs is crucial for AI enterprises. For businesses that process large volumes of text, understanding this discrepancy is crucial when evaluating the true cost of deploying models.
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