Unverified50% confidenceTradeoffExact time
CoT ties the model's thinking budget entirely to the number of output tokens—each additional reasoning step requires generating more text, increasing computational cost and subject to the serial bottleneck of autoregressive decoding.
1
Sources
50%
Confidence
Long-term
Relevance
9/4/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedReasoning budget refers to the upper limit on the number of intermediate reasoning tokens a chain-of-thought model is allowed to consume before generating a final answer; the higher the budget, the deeper the self-reflection and multi-step verification the model can perform.73% similarUnverifiedExtended thinking mode causes the model to perform an explicit internal reasoning chain before output, at the cost of significantly increased token consumption, with reasoning tokens typically billed at a higher rate.73% similarVerifiedThe core finding of CoT is that when models are asked to think step by step, accuracy on tasks such as arithmetic and commonsense reasoning improves substantially.72% similarUnverifiedThe internal chain of thought in reasoning models generates a large number of output tokens, making the actual cost of completing complex tasks often far higher than what a per-token price comparison would suggest.72% similarUnverifiedChain-of-Thought (CoT) prompting improves the quality of complex problem solving by requiring the model to reason step by step.71% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/852732API
curl https://kongchang.com/api/v1/knowledge/claims/852732MCP
get_claim(id=852732)