Unverified50% confidenceOpinionExact time
Benchmarks typically count only the cost of one successful call and completely ignore the repeated trial and error in real workflows; counting only the cost of one successful call is equivalent to assuming a retry rate of zero, which is severely disconnected from actual bills.
1
Sources
50%
Confidence
Long-term
Relevance
10/16/2026
First Seen
Sources
Related Entities
Related Claims
Unverified对同一测试用例执行多次调用统计成功比例得到通过率，比二元的通过/失败判断更能反映模型真实表现74% similarUnverifiedRetry rate refers to the proportion of cases where the model's first output is not adopted and the developer needs to ask again or adjust the prompt and try again; it is ubiquitous in real workflows because the model's one-shot success rate is far below the ideal value assumed by benchmarks.74% similarUnverifiedFailed retries across multiple models may accumulate actual costs, and if only the cost of the successful attempt is recorded, billing attribution becomes distorted.72% similarUnverifiedSetting an absolute failure count ceiling for small-sample slices is more robust than setting a percentage threshold and is insensitive to sample size72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1049239API
curl https://kongchang.com/api/v1/knowledge/claims/1049239MCP
get_claim(id=1049239)