mlsanityData to 14 Oct 2026

The Price of Thinking: Reasoning Effort as a Model-Specific API Contract

arXiv 2608.16956 ↗First posted 16 Aug 2026cs.AI cs.CL cs.CYcited by 0

On the map: LLM reasoning → Test-time compute and efficient thinking

Abstract (arXiv)

API buyers purchase a dated contract, not a model name alone: the contract includes the requested and served model, reasoning-effort term or its omission, output rail, service product, prompt, and price schedule. We study the reasoning-effort term through a registered paired contrast of Sonnet 5 with explicit high effort against the same model with effort omitted, using 30 AIME 2026 items and five calls per item. Every paid attempt was assigned one frozen terminal category, and inference resampled items while retaining their repeated calls. Mean delivered cost was 0.01031 per call higher under the explicit-high contract than under the omitted contract [+0.00204, +0.01974]. The corresponding accuracy contrast was +0.0133 [-0.0267, +0.0467]; we did not detect an accuracy difference, and the interval permits a gain of up to 4.67 percentage points that this design cannot rule out. Cost per correct answer was 0.08665 under the high-effort contract and 0.07662 under the omitted contract, as registered point estimates. A dated contract census, Models-API metadata, and preregistered raw-response probes further documented model-specific omission semantics, including within a provider; claims remained at documentation grade when raw structure was indeterminate. The request registry, parser, terminal taxonomy, statistical plan, and analysis pipeline were frozen before outcomes were examined; the resulting claims are bounded to the model, task, and collection date studied.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Test-time compute and efficient thinking, one of 17 directions in LLM reasoning. Builds on 1 of its 1 references that are in the map. First posted on arXiv 16 Aug 2026.

Builds on

1 of 1 references.

References · 1

  1. 2020Impact of News on the Commodity Market: Dataset and Resultscited by 80

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2026The Price Reversal Phenomenon: When Cheaper Reasoning Models Cost More
  2. 2025Cost-of-Pass: An Economic Framework for Evaluating Language Models
  3. 2026The Price of Intelligence: A Quality-Adjusted Price Index for AI Services
  4. 2026Test-time reasoning effort and unauthorized tool use in language-model agents: a prespecified equivalence study
  5. 2026Brief Is Better: Non-Monotonic Chain-of-Thought Budget Effects in Function-Calling Language Agents
  6. 2024STEER: Assessing the Economic Rationality of Large Language Models
  7. 2025The Price of Thought: A Multilingual Analysis of Reasoning, Performance, and Cost of Negotiation in Large Language Models
  8. 2026Thinking Costs Tokens: When More Structure is Worth the Price