deer-flow
★ 84.5k
vs
awesome-multi-agent-papers
★ 1.7k
deer-flow vs awesome-multi-agent-papers
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.; awesome-multi-agent-papers: This repository compiles an awesome list of the best multi-agent research papers, curated by the Swarms Team. Its mission is to advance multi-agent systems research, promote their widespread adoption, and facilitate their integration into the global economy.
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.
awesome-multi-agent-papersMulti-Agent · ★ 1.7k
Literature review for multi-agent system researchers and students.
02
Side-by-Side Comparison
Field
deer-flowawesome-multi-agent-papersCategory
Multi-Agent
Multi-Agent
Stars
★ 84.5k
★ 1.7k
License
MIT
NOASSERTION
Install Command
uv sync
git clone https://github.com/kyegomez/awesome-multi-agent-papers.git
Updated
1d ago
5d ago
Open Source
Yes
Yes
Tags
LLM, Multi-Agent, Research Automation
Multi-Agent Systems, Large Language Models, AI Research
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
awesome-multi-agent-papers01A curated, comprehensive list of multi-agent research papers.
02Papers are systematically categorized into key areas like collaboration, frameworks, and applications.
03Strong focus on Large Language Model (LLM)-based multi-agent systems.
04Provides direct access to papers via links (arXiv, GitHub, Semantic Scholar, etc.).
05Explores diverse real-world application domains for multi-agent AI.
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
awesome-multi-agent-papers↳Literature review for multi-agent system researchers and students.
↳Exploring cutting-edge multi-agent frameworks and design patterns.
↳Identifying state-of-the-art applications of multi-agent AI in various domains.
05
Best For
deer-flowMost PopularEssentialTrending
awesome-multi-agent-papersTrending
FAQ
FAQ
What is the difference between deer-flow and awesome-multi-agent-papers?
Both deer-flow and awesome-multi-agent-papers are in the Multi-Agent category. deer-flow has 84.5k stars, while awesome-multi-agent-papers has 1.7k stars.
Which is better, deer-flow or awesome-multi-agent-papers?
The best choice depends on your use case. Choose deer-flow if Conducting deep research and generating comprehensive reports with multimedia content, and awesome-multi-agent-papers if Literature review for multi-agent system researchers and students..
Is deer-flow free or open source?
Yes, deer-flow is open source on GitHub (MIT).
Is awesome-multi-agent-papers free or open source?
Yes, awesome-multi-agent-papers is open source on GitHub (NOASSERTION).
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