Unverified90% confidenceFactTime unknown
多模态大模型的推理成本远高于传统OCR引擎
1
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90%
Confidence
Long-term
Relevance
6/1/2026
First Seen
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UnverifiedReasoning models (such as the o1 series) can cost several times to more than ten times more than regular models because they need to generate a large number of intermediate thinking steps.74% similarUnverifiedThe total inference cost of large models exceeds the training cost, because inference continues to occur and grows linearly with user scale.71% similarUnverifiedThe internal chain of thought in reasoning models generates a large number of output tokens, making the actual cost of completing complex tasks often far higher than what a per-token price comparison would suggest.69% similarUnverified大型语言模型的推理成本与参数规模并非线性关系，参数量从千亿级跃升至万亿级时推理所需的GPU显存、带宽和计算量会指数级攀升67% similarPartially VerifiedLarger model parameters bring stronger reasoning capabilities but also higher computational costs and longer response latency.65% similar
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