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Sprint projectOct 26, 2026Online(from Kerala, India)

An LLM Pricing Hub Survives Data Limits on Some Models; Firm Discretion Works Only When Firms Refuse Small Nudges

Ebin Babu Thomas

Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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We test whether the remedies in the DOJ's 2026 RealPage Final Judgment stop an LLM pricing hub that advises competing firms and is instructed to maximise their combined profit, the incentive alleged against RealPage. In a repeated Bertrand duopoly (700+ runs, seven models from six labs, main batch pre-registered), the hub drives a competitive market to joint monopoly. With a per-client objective and the same rival data it is pro-competitive: the objective, not the data, does the harm. A data ban removes most of the harm on three models and almost none on two. Per-round auto-accept bands only delay monopoly. Firm discretion works only when the deciding firm refuses small nudges: a scripted one-cent-per-round ratchet takes three of five firm models most or all of the way to monopoly, and a monitor of single price moves misses these climbs. Remedies should target the advisor's objective and audit acceptance rates and where prices settle.

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Cite this project

@misc{thomas2026llm,
  title = {{An LLM Pricing Hub Survives Data Limits on Some Models; Firm Discretion Works Only When Firms Refuse Small Nudges}},
  author = {Ebin Babu Thomas},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/an-llm-pricing-hub-survives-data-limits-on-some-models-firm-discretion-works-only-when-firms-refuse-small-nudges-6cca}},
  url = {https://apartresearch.com/sprints/projects/an-llm-pricing-hub-survives-data-limits-on-some-models-firm-discretion-works-only-when-firms-refuse-small-nudges-6cca}
}

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