Teams building LLM applications with .NET are encountering token budget limitations in production, often leading to service disruptions and unexpected costs. Managing tokenization—the process of breaking down text into units for the model—is now a critical resource, akin to CPU or memory, and requires careful consideration of trade-offs between performance, cost, and accuracy. Specifically, developers should prioritize in-process tokenization and consider custom BPE vocabularies to optimize token counts and reduce reliance on external services.
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