Unverified50% confidenceBenchmarkExact time
The idealized optimal task-model matching achieves a solution rate of 97.6%, at a cost of only $1.88 per task.
1
Sources
50%
Confidence
Long-term
Relevance
9/24/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedThrough a gradient-based model scheduling strategy, 80% of simple tasks are handled by the cheapest model and only 5% of complex tasks invoke the top-tier model, reducing overall costs by 60–70%.78% similarUnverified大模型的推理成本与参数量大致成正比，而实际业务中约80%的任务可以由中小规模模型胜任73% similarUnverifiedUsing a GPT-3.5-level model for simple tasks costs approximately 1/20 of flagship model pricing, and proper LLM routing can reduce overall inference costs by 60%–80%.69% similarUnverifiedEvaluating the per-task cost of large models requires considering both the token unit price and the number of tokens consumed to complete the task; the output token consumption of chain-of-thought reasoning models may increase by several times or even dozens of times.68% similarUnverified评估模型成本的正确指标不是单位Token价格，而是完成任务的总成本（Total Cost of Task）68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/946769API
curl https://kongchang.com/api/v1/knowledge/claims/946769MCP
get_claim(id=946769)