Unverified50% confidenceDecision RuleExact time
When inference costs are factored into total cost of ownership, increasing the token-to-parameter ratio (training a smaller model on more data) is often the more economical choice.
1
Sources
50%
Confidence
Long-term
Relevance
10/7/2026
First Seen
Sources
Related Entities
Related Claims
Unverified对多数应用场景而言，提示词优化的性价比高于模型微调79% similarUnverifiedReasoning models may consume several times or even more than ten times the output tokens, directly driving up API call costs.75% similarUnverifiedCosts themselves are often estimates rather than constants; one can consider modeling costs as intervals or distributions to enable robust decision-making.75% similarUnverifiedInvesting 10%–20% more cost during the training phase to obtain a smaller, faster model at inference time is extremely cost-effective from a full lifecycle cost perspective.74% similarUnverified差异化Token倍率机制可通过更高的消耗系数对高成本模型使用量形成经济约束，并引导用户在轻量任务中优先选用小模型74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/984139API
curl https://kongchang.com/api/v1/knowledge/claims/984139MCP
get_claim(id=984139)