Agent-built small classifier labels 191K documents for $0.70, vs $13–26 with batch LLMs
vanstriendaniel · x · 2026-09-11
A showcase of the "tokenmaxxing" move: use frontier agents to build small classifiers for large-scale data curation instead of labeling with LLMs directly.
- Stack: Astra (agent) + SetFit + Hugging Face Jobs; just 200 agent-labelled examples produced a reusable document-purpose classifier
- Classified 191,724 FinePDFs-Edu documents for $0.70 in inference compute, vs an estimated $13–26 to label the same excerpts with low-cost batch LLMs
- Training experiments added $2.90 in compute
- Full workflow, mistakes, reusable model and prompt are published
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