Unverified50% confidenceSolutionExact time
In deep research scenarios, lightweight low-cost models can handle simple query rewriting and relevance pre-screening, while high-capability reasoning models handle complex information synthesis and report writing, to balance quality and cost.
1
Sources
50%
Confidence
Long-term
Relevance
7/22/2026
First Seen
Sources
Related Claims
UnverifiedWhen deploying deep research agents, costs can be optimized by routing simple tasks to lower-cost models through a model routing strategy.83% similarUnverifiedThe Deep Research feature decomposes a single user query into multi-step autonomous research tasks, invokes tools such as web search and document analysis, and uses large language model reasoning to synthesize and output a structured report.81% similarUnverified研究阶段应使用 Deep Research 等动态多智能体工作流，用廉价模型收集信息，再交给 Opus 5 制定计划79% similarUnverifiedOpenAI's Deep Research primarily helps users complete complex reasoning and research tasks, achieving continuous research capabilities through multi-round retrieval, cross-validation, and self-correction.74% similarUnverifiedWhen deploying deep research agents, it is necessary to set reasonable loop limits and concurrency strategies to control token consumption costs.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/592629API
curl https://kongchang.com/api/v1/knowledge/claims/592629MCP
get_claim(id=592629)