GPT Researcher

Built by Assaf Elovic and recognized by Carnegie Mellon University's DeepResearchGym evaluation, GPT Researcher outperformed Perplexity, OpenAI, HuggingFace, and OpenDeepSearch on a benchmark of 1,000 complex queries demonstrating state-of-the-art performance across citation quality, report quality, and information coverage.

The platform's Deep Research mode implements a recursive exploration workflow that maps a topic using a tree-like structure diving progressively deeper into subtopics while maintaining a comprehensive overview of the entire research subject.

Rather than producing a surface-level summary of the first few sources found, this agentic approach systematically explores multiple branches of a topic to ensure thorough coverage before synthesizing findings.

GPT Researcher generates research reports that can exceed 2,000 words and cite more than 20 sources, providing the depth and citation density expected of serious academic or professional research deliverables.

The platform also supports automatic generation and embedding of AI-created illustrations within research reports using Google's Gemini models, enriching visual presentation of complex information alongside the written analysis.

The platform supports over 100 different large language models as its reasoning backbone including Gemini, Claude, Llama, and others making it model-agnostic and allowing users to configure it with whichever LLM they prefer or have access to. This flexibility enables both cloud-based and fully local research workflows for users with privacy requirements or infrastructure preferences.

GPT Researcher is free and open-source, available for self-hosting on GitHub under an open license.