GLM-5.1 OCR stack burns RunPod cash

This looks less like a GPU pricing problem than a model-selection problem: document OCR and field extraction rarely need a flagship reasoning model on the hot path.

• –Split the pipeline: use a cheaper OCR/doc parser for layout and field extraction, then reserve GLM-5.1 for exception handling, reconciliation, and natural-language Q&A
• –Add routing and confidence thresholds so clean invoices and statements never hit the expensive model
• –Cache aggressively at the document, page, and entity level; tax and accounting workflows repeat a lot of the same normalization work
• –If you must keep GLM-5.1, move off always-on on-demand compute and use batching, autoscaling, spot capacity, or a smaller self-hosted tier for baseline traffic
• –The real wedge for a SaaS like this is not raw model power, but per-document unit economics that stay sane before revenue catches up