ScaleDown releases three constrained decoding models for extraction tasks
Constrained decoding shifts extraction, classification and summarisation from generative to selection-based inference, cutting both cost and latency by orders of magnitude. Teams running agent pipelines with high-volume document parsing can swap expensive frontier LLM calls for these models, keeping outputs locked to their own labels or source text. Compared with frontier APIs that charge per output token, free output changes the economics of bulk document workflows.
