Unverified50% confidenceBenchmarkExact time
In 500 automated stress tests, the unconstrained conversational Agent consumed an average of 1450 tokens per task, while the typed Bot Skill+MCP architecture consumed an average of 580 tokens per task, reducing cost and latency by 60%
1
Sources
50%
Confidence
Long-term
Relevance
10/15/2026
First Seen
Sources
Related Entities
Related Claims
Unverified一个包含5个Agent、每Agent平均10轮推理、每轮2000 Token的任务单次执行约消耗10万Token，而等效确定性工作流可能只需一次几百Token的调用72% similarVerifiedAn Agent's token consumption for a single task may be 5–10 times that of an ordinary conversation, due to the involvement of multiple rounds of large model calls.71% similarVerifiedIn multi-agent systems, each Agent call must carry the full context, and multi-turn reasoning continuously accumulates conversation history, meaning a seemingly simple multi-Agent task may consume tens of thousands or even hundreds of thousands of Tokens, whereas an equivalent workflow might only require a single call of a few hundred Tokens.67% similarUnverifiedIn an actual test of 100 tickets in a Docker environment, SupportOps-AI had a median of 4500 tokens/ticket, 3.1 API calls/ticket, an inference cost of $0.007/ticket, and a wall-clock time of 7.4 seconds/ticket.66% similarUnverifiedFor an Agent that executes 5 tool calls, the total Token consumption may be 15–20 times that of a single call rather than a simple 5 times.66% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1037007API
curl https://kongchang.com/api/v1/knowledge/claims/1037007MCP
get_claim(id=1037007)