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Prompt optimization is a practical concern for professionals using large language models like ChatGPT, Claude, and GitHub Copilot. Understanding tokenization is key to reducing AI spend, as token counts affect context limits, response quality, latency, and cost. By crafting shorter, more efficient prompts, users can lower token usage and control expenses without sacrificing performance. This tag covers strategies for minimizing token-heavy prompts and optimizing interactions with LLMs.
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Tokenization 101: How LLMs Charge by Tokens and How to Cut AI Spend
Understanding tokenization is the key to understanding how modern large language models turn language into something they can compute, compare, and bill. In LLMs such as ChatGPT, Claude, and GitHub Copilot, the unit of account is rarely the word or sentence; it is the token, a smaller text...- ChatGPT
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- context window llm cost prompt optimization tokenization
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- Forum: Windows News