Unverified50% confidenceFactExact time
大语言模型在实验室benchmark表现与真实用户场景表现存在显著差距，被业界称为benchmark-reality gap
1
Sources
50%
Confidence
Long-term
Relevance
8/5/2026
First Seen
Sources
Related Claims
UnverifiedThe core bottleneck in current multimodal large models has shifted from the perception gap to the reference gap.69% similarUnverifiedThere is still a gap between laboratory demonstrations and real complex environments (noisy backgrounds, dialectal accents, and specialized terminology), and the model's stability in real-world scenarios has yet to be verified.66% similarUnverifiedUnder the same model, the gap in task success rate between a professional prompt and a vague prompt can be several times larger66% similarUnverifiedThe cost and latency of applying large language models to real-time security moderation remain major obstacles, resulting in a capability gap between the security layer and the generation layer.63% similarUnverifiedLarge language models are prone to hallucination drift when handling detail consistency problems that require precise long-range context tracking.63% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/687613API
curl https://kongchang.com/api/v1/knowledge/claims/687613MCP
get_claim(id=687613)