Unverified60% confidenceFactExact time
Even with identical inputs, different random seeds or sampling parameters can lead to entirely different outputs from large models.
2
Sources
60%
Confidence
Long-term
Relevance
9/1/2026
First Seen
Sources
Related Entities
Related Claims
Unverified即便固定所有随机种子，在不同硬件或并行度下，训练结果仍可能出现被大模型放大为显著能力差异的细微偏差78% similarUnverifiedThe results of a single-task evaluation are subject to randomness, and the same model may produce noticeably different answers under different prompts and different random seeds.78% similarUnverifiedThe output of LLMs is inherently stochastic, and identical inputs may produce entirely different results across different calls.78% similarUnverified大模型的输出是非确定性的，同一个输入可能产生不同输出，且输出格式难以精确控制76% similarVerifiedLarge model outputs are stochastic (controlled by the Temperature parameter), so a single comparison is not conclusive and requires multiple sampling and statistical comparisons.75% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/840325API
curl https://kongchang.com/api/v1/knowledge/claims/840325MCP
get_claim(id=840325)