DeerFlow

Open Source

4.1 / 5

Last updated: Jun 10, 2026

About

DeerFlow is an open-source long-horizon SuperAgent Harness created by ByteDance, positioned as a general-purpose AI agent framework capable of handling almost any task. By orchestrating sub-agents, managing memory systems, providing sandboxed environments, and offering an extensible skill system, it can handle everything from research and reports to slides, web pages, images, and video generation.

Key Features

Deep Research — internet search and analysis, generating research reports
Long/Short-Term Memory — sustained understanding of user and task context
Task Planning & Sub-tasking — pre-plan and reason through complexity, execute sequentially or in parallel
Sandbox Environment — Docker-based isolated sandbox with Browser, Shell, File System, VSCode Server
Extensible Skill System — pluggable loading on demand, supports community contributions
Multi-Model Support — Doubao, DeepSeek, OpenAI, Gemini, and more
Content Generation — web pages, video, images, slides
Code Execution — run code and scripts in the sandbox

Use Cases

Deep Research Reports, Video Generation, Data Analysis, Web Development, Content Creation, Technical Research

Pros & Cons

Pros

Built by ByteDance with strong technical backing
Full-stack SuperAgent capabilities with wide coverage
MIT open source, completely free
Well-integrated sandbox + memory + skills architecture
Flexible multi-model support
Active community with continuous iteration

Cons

Deployment requires Docker knowledge
Resource-intensive (requires running sandbox environment)
Long execution times for complex tasks
As a newer project, ecosystem still growing
Some skill quality depends on model capability

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Pricing

Open Source / Free (MIT License)