📄 中文摘要
在 2026 年使用 LLM 的开发者面临着 API 成本悄然上升的问题。随着功能的推出和使用量的激增，OpenAI 的账单可能会超出预算。问题的根源在于缺乏可见性，许多开发者在账单到来之前并不知道每次请求消耗了多少令牌。通常的情况是，开发者在使用 GPT-4 或 Claude 进行原型设计时，随着上下文和少量示例的增加，提示变得越来越长，却忘记分别跟踪输入和输出令牌，最终导致月底时收到意外账单。开发者们因此浪费了数百美元，主要是因为未意识到单个提示可能消耗了 8000 个令牌。
停止在 LLM API 上浪费资金 — 实时跟踪您的令牌使用情况
出处: Stop Burning Money on LLM APIs — Track Your Token Usage in Real Time
发布: 2026年3月25日
📄 English Summary
Stop Burning Money on LLM APIs — Track Your Token Usage in Real Time
Developers working with LLMs in 2026 face the issue of silently rising API costs. As features are launched and usage spikes, OpenAI bills can exceed budgets unexpectedly. The root of the problem lies in a lack of visibility; many developers are unaware of how many tokens are consumed per request until the invoice arrives. Typically, developers prototype with GPT-4 or Claude, and as they add context and few-shot examples, prompts become longer. They often forget to track input versus output tokens separately, leading to surprise bills at the end of the month. This lack of awareness can result in hundreds of dollars wasted, as a single prompt can consume up to 8,000 tokens.