arXiv:2605.24218v1 Announce Type: new Abstract: Deep research agents extend the role of search engines from retrieving keyword-matched pages to synthesizing knowledge, fundamentally changing how humans interact with information. However, frontier systems remain proprietary, while existing open agents often generalize poorly across different task types, leaving unclear how to train a broadly capable deep research agent. We release QUEST, a family of open models (ranging from 2B to 35B) that serve as general-purpose deep research agents designed to handle a wide range of long-horizon search task
The release of QUEST comes as the AI community grapples with building truly autonomous and general-purpose agents, moving beyond narrow applications to more complex, multi-step reasoning and information synthesis.
This development addresses a critical gap in open-source AI, providing a foundational capability for synthesizing knowledge across diverse tasks, which can democratize access to advanced AI research tools and insights.
The availability of open models like QUEST for deep research agents shifts the landscape from proprietary, black-box systems towards more transparent and accessible platforms for information synthesis and problem-solving.
- · Open-source AI community
- · Academic researchers
- · Startups building on agentic AI
- · Sectors requiring complex information synthesis
- · Proprietary deep research agent developers
- · Legacy search engines (long-term pressure)
- · Consulting firms reliant on manual synthesis
- · Human information synthesis services
The immediate impact will be a significant acceleration in the development and application of autonomous AI agents for complex information tasks.
This acceleration could lead to new tools and services that fundamentally alter workflows in research, analysis, and strategic decision-making across industries.
Over time, such widely accessible and capable agents may reduce the information asymmetry between large institutions and smaller entities, potentially reshaping competitive landscapes and driving new forms of innovation.
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Read at arXiv cs.CL