Token budgeting is a strategic approach to allocating computational resources in AI systems, ensuring efficient use of limited token limits. It involves planning token distribution across prompts, responses, or tasks to optimize performance, reduce costs, and avoid overload. Developers, data scientists, and businesses using large language models benefit by maximizing output value.
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