Unverified60% confidenceFactExact time
The total inference cost of large models exceeds the training cost, because inference continues to occur and grows linearly with user scale.
2
Sources
60%
Confidence
Long-term
Relevance
7/21/2026
First Seen
Sources
Related Claims
VerifiedThe 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.81% similarUnverifiedModel training is one-time, but inference occurs continuously with user requests, so inference costs often account for the vast majority of total AI costs.79% similarUnverifiedFor models that are called repeatedly, inference costs already dominate the total lifecycle expenditure of a model, and when N×c_infer×T is much greater than C_train, the total cost of ownership is dominated by inference.78% similarUnverifiedIn large model inference, the stronger the model capability (more parameters, deeper reasoning), the higher the marginal cost, which stands in contrast to the cost structure of traditional software development where copying is essentially free.77% 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77% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/582548API
curl https://kongchang.com/api/v1/knowledge/claims/582548MCP
get_claim(id=582548)