Edward Conard

Top Ten New York Times Bestselling Author

  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “Unintended Consequences is far smarter and more thought-provoking than most economics written for the general public” - Greg Mankiw, Harvard University, Former Chairman of the Council of Economic Advisors
  • “Unintended Consequences is full of substance, it is one of the must-read books of the year, and once I finish it I will be giving it a second read through right away.” - Tyler Cowen, Professor, George Mason University
  • “There are an amazing number of good ideas and interesting points made in Unintended Consequences. The thinking underlying it, and the obvious depth of understanding of the author, are very impressive.” - Steven Levitt, coauthor of Freakonomics; 2004 John Bates Clark Medal
  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
Upside of Inequality Oxford Unintended Consequences

AI Summary. Leading artificial-intelligence labs are moving to usage-based token pricing on a cost-plus basis that includes total ownership costs, pushing token prices higher and giving some enterprises reason to migrate to cheaper open models. Frontier models remain necessary for cybersecurity, distillation training, agents, and scientific discovery, where maximum performance is required.

Michael Cembalest J.P. Morgan
Date Posted:

Cembalest notes the “cost vs performance tradeoffs appear to provide ample incentive for open model adoption” as usage costs for frontier models rise. Enterprise tokens, and in turn models, will likely be commoditized.

Will rising token prices push enterprises toward cheaper open models?

Core argument: Cursor and Anthropic charge 6x more for tokens delivered 2.5x faster, indicating some enterprises will pay a premium for ultra-fast tokens.

The frontier labs are shifting to usage-based token pricing. It’s expected to become the norm, at least for enterprises, on a cost-plus basis that includes total costs of ownership. This will increase frontier lab token prices, a trend that is already underway. As a result, some enterprises may seek to avoid frontier lab token price increases by migrating to cheaper open models. Frontier models are here to stay since they’re needed for cybersecurity, distillation training, agents, and scientific discovery, all of which require maximum performance. There are enterprises even willing to pay up for ultra-fast tokens. For example, Cursor and Anthropic charge 6x more for tokens that are 2.5x faster. That said, many tokens consumed in the future may not come from frontier models but from smaller open models that are up to the tasks.

Takeaways by Macro Roundup® AI

  1. Cursor and Anthropic charge 6x more for tokens delivered 2.5x faster, indicating some enterprises will pay a premium for ultra-fast tokens.
  2. Frontier labs are shifting to usage-based token pricing on a cost-plus basis that includes total cost of ownership, which is expected to raise frontier token prices, a trend already underway.
  3. Frontier models remain necessary for cybersecurity, distillation training, agents, and scientific discovery, though many tokens consumed in the future may come from smaller open models that enterprises adopt to avoid frontier price increases.

Related Articles:

  • Chart of the Day: Small Models are Closing the Gap to Frontier AI — Achieving 60% on MMLU, a test of academic reasoning, once required a 540bn-parameter model but was reached by a 3.8bn-parameter model two years later, a 142x reduction in parameters. Models small enough to run on phones or sensors shift inference from data centers to devices, weakening the case for paying cloud providers per token.
  • Commoditization, Orchestration, and the New AI Stack — The author argues that as incremental gains from larger AI training runs shrink, the return on additional computing power falls, weakening the case for the training spending that dominates data center demand. Survivors of model commoditization will be those owning the orchestration layer or the applications where outcomes are priced.
  • The Geopolitics of AI: Decoding the New Global Operating System — The performance gap between the top American and Chinese AI models narrowed from 9.3% to 1.7%, with Chinese firms relying on cheaper open-source models—DeepSeek prices usage 20-40x below OpenAI's ChatGPT. This price advantage could win adoption in developing countries and build dependency on Chinese AI ecosystems.
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