Expired50% confidenceFactExact time
Reasoning models exhibit an intelligence-degradation phenomenon where the server may dynamically reduce the compute resources allocated to a single request during peak periods, causing a decline in output quality.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/18/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 10/16/2026(expired)
Sources
Related Claims
UnverifiedLow-cost subscription tiers typically imply limited underlying model capabilities, and complex reasoning and multi-turn context tracking may perform unstably.75% similarUnverifiedSmaller models often show exponential rather than linear degradation in performance on long reasoning chain tasks.74% similarUnverified响应速度快无法证明背后是否为官方正版服务,能力越强的模型每次推理消耗算力越多、响应时间相应更长73% similarUnverified策略拥挤效应会导致因子预测能力衰减、夏普比率下降,甚至在市场压力时期出现因子崩溃73% similarUnverified推理部署对单次计算规模要求低,但需要应对海量并发请求,更强调吞吐量和延迟的平衡72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/552252API
curl https://kongchang.com/api/v1/knowledge/claims/552252MCP
get_claim(id=552252)