Splitting OCR and Reasoning Tasks Cuts Claude API Costs by Over 80%

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A developer building a personal PDF-to-knowledge-base pipeline discovered that routing all tasks through Claude's most powerful model, Opus, cost around $1.10 per 26-page document. By separating the workflow into two distinct steps — using the cheaper Haiku model for image-based OCR and Sonnet for complex concept extraction — the per-document cost dropped to roughly $0.18. The key insight was that rote text transcription from images requires no advanced reasoning, making it well-suited for a lower-tier model. The split is implemented via two environment variables pointing each task to a different Claude model. This task-routing approach achieved an estimated 84% cost reduction without sacrificing the quality of the final structured output.

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