Verified70% confidenceCautionExact time
Models may fall into the trap of overthinking, as longer reasoning time does not always lead to better results.
4
Sources
70%
Confidence
Long-term
Relevance
9/5/2026
First Seen
Sources
Related Entities
Related Claims
Unverified模型有时会陷入过度思考，在特定任务中产生超过52倍的额外token78% similarUnverifiedThe longer the context, the slower the model's inference speed—that is, there is a trade-off between context length and inference performance.78% similarUnverifiedExcessive upfront thinking incurs increased latency and computational costs, which may not be worthwhile in scenarios that prioritize response speed.78% similarUnverifiedThe thinking budget mechanism of reasoning models sets an upper limit on the number of reasoning tokens, and once exhausted, the model cannot output a complete answer, potentially causing overthinking issues.77% similarUnverifiedExcessive guidance (providing the solution in the prompt) may instead constrain the model's capabilities and foreclose the model's exploration of other possibilities (such as virtual memory or databases).77% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/860776API
curl https://kongchang.com/api/v1/knowledge/claims/860776MCP
get_claim(id=860776)