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How a Simple Token Ledger Can Prevent Costly Free-Tier API Overruns

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Developers using free AI model tiers often discover quota overruns only after a batch job fails, wasting both time and retry budget. A lightweight Python token ledger can predict whether a batch job fits within a given allowance before any live API call is made. The approach uses a rough heuristic of one token per four characters to estimate prompt and completion costs across thousands of calls. For example, a job requiring 6,000 summaries with 21,000-character prompts would need an estimated 32.25 million tokens, exceeding a 30-million-token free allowance. The ledger does not replace a real tokenizer but serves as a fast, deterministic pass/fail filter that separates budget planning from actual API spending.

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