deer-flow
★ 84.5k
vs
deep-research
★ 4.7k
deer-flow vs deep-research
deer-flow: DeerFlow is a community-driven framework designed for deep research, integrating language models with specialized tools for tasks like web search, crawling, and Python code execution. It offers a modular multi-agent system architecture for automated research, supporting various search engines, crawling tools, and private knowledge bases.; deep-research: Deep Research is an AI-powered tool designed to generate comprehensive research reports rapidly, leveraging advanced AI models and internet connectivity. It prioritizes user privacy by processing and storing all data locally.
01
TL;DR
deer-flowMulti-Agent · ★ 84.5k
When to choose:
- You want a batteries-included LangGraph agent runtime with a file system, isolated bash/Docker sandbox, persistent memory, and sub-agent delegation.
- You want to trigger long-running tasks from Feishu, WeCom, DingTalk, WeChat, Slack, or Telegram without exposing a public IP.
When to skip:
- Your machine or VPS has only 2 vCPU / 4 GB RAM; DeerFlow recommends 8 vCPU / 16 GB RAM for shared servers.
- You only want a lightweight script that writes cited web research reports without running local sandboxes; GPT Researcher is much lighter.
deep-researchRAG / Knowledge Base · ★ 4.7k
Rapidly generate in-depth research reports for personal and professional use.
02
Side-by-Side Comparison
Field
deer-flowdeep-researchCategory
Multi-Agent
RAG / Knowledge Base
Stars
★ 84.5k
★ 4.7k
License
MIT
MIT
Install Command
uv sync
docker run -d --name deep-research -p 3333:3000 xiangfa/deep-research
Updated
1d ago
4mo ago
Open Source
Yes
Yes
Tags
LLM, Multi-Agent, Research Automation
AI Research, LLM, Privacy-focused
03
Features
deer-flow01Multi-model LLM integration via LiteLLM with OpenAI-compatible API
02Comprehensive web search and crawling using diverse engines like InfoQuest and Tavily
03RAG integration with multiple vector databases including Qdrant and RAGFlow
04Human-in-the-loop collaboration with intelligent clarification and interactive plan modification
05Automated content creation for podcasts and presentations with AI-powered script generation
deep-research01Rapidly generates comprehensive research reports in minutes.
02Ensures privacy by processing and storing all data locally in the browser.
03Supports a wide range of mainstream large language models (LLMs).
04Integrates with various web search engines for enhanced information gathering.
05Allows uploading and processing local files to build a knowledge base.
04
Use Cases
deer-flow↳Conducting deep research and generating comprehensive reports with multimedia content
↳Automated creation of podcasts, articles, and presentations from research findings
↳Intelligent information retrieval and analysis for complex queries and trending topics
deep-research↳Rapidly generate in-depth research reports for personal and professional use.
↳Serve as a deep research as a service (SaaS) platform via SSE API.
↳Integrate deep research functionality into other AI applications using MCP.
05
Best For
deer-flowMost PopularEssentialTrending
deep-research—
FAQ
FAQ
What is the difference between deer-flow and deep-research?
Both deer-flow and deep-research are in the Multi-Agent category. deer-flow has 84.5k stars, while deep-research has 4.7k stars.
Which is better, deer-flow or deep-research?
The best choice depends on your use case. Choose deer-flow if Conducting deep research and generating comprehensive reports with multimedia content, and deep-research if Rapidly generate in-depth research reports for personal and professional use..
Is deer-flow free or open source?
Yes, deer-flow is open source on GitHub (MIT).
Is deep-research free or open source?
Yes, deep-research is open source on GitHub (MIT).
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