Verified80% confidenceFactExact time
LLM output is non-deterministic; due to the non-associativity of floating-point operations and differences in context windows, even with identical inputs, outputs are difficult to reproduce exactly and do not possess idempotency.
4
Sources
80%
Confidence
Long-term
Relevance
7/21/2026
First Seen
Sources
Related Claims
UnverifiedLLM output may have invisible tokens such as newline characters, spaces, or zero-width spaces appended at the end, causing strict string equality checks to fail.78% similarUnverified由于LLM的输出带有不确定性，Agent场景下无法保证两次调用生成的参数完全一致，这使得幂等键的生成和匹配比传统系统更复杂77% similarVerifiedLLM calls have inherent uncertainty: the same input may produce different outputs, token consumption and latency fluctuate significantly, and the reasoning path of an Agent is difficult to predict.74% similarUnverifiedSwitching to a stronger model cannot solve the LLM reliability problem, because as long as the system allows uncontrolled output to flow directly into downstream logic, it will still collapse at the boundary.73% 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73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/582149API
curl https://kongchang.com/api/v1/knowledge/claims/582149MCP
get_claim(id=582149)