Unverified50% confidenceTradeoffExact time
自建AI的主要代价包括硬件投入（尤其GPU资源）、技术运维能力以及与顶级闭源模型可能存在的性能差距
1
Sources
50%
Confidence
Long-term
Relevance
7/16/2026
First Seen
Sources
Related Claims
Unverified专用硬件如GPU、ASIC的普及正在削弱工作量证明的成本壁垒70% similarUnverified自购GPU硬件只有在高利用率的场景下才有经济意义69% similarUnverified被投公司的模型架构一旦深度耦合于英伟达硬件，切换至AMD ROCm或其他替代架构的工程迁移成本极高67% similarUnverifiedOnce the scale of a model and its compute demands reach a certain level, custom chips can often surpass general-purpose GPUs in both performance and cost.66% similar
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