Last week ScaleDown launched Constrained Decoding Models (CDMs). The launch post got about 1.8M views. The pitch is simple: most production LLM calls don't need prose. They need a label, a field, or a short summary. So instead of a general model writing an answer token by token, each CDM does one job, reads your input once, and returns a typed result. Pricing is $0.05 per million input tokens (OpenRouter lists $0.04 with a 20% promo), and output is free.

The launch post made big claims: "200x faster, 467x cheaper than frontier LLM APIs" and "77.2% on DecisionBench". A thread from Bitroot pushed back the next day. Their point was that the 467x has no stated baseline, DecisionBench has no public source, and nobody should trust a classifier result without a few hundred labelled examples and confidence intervals.…