DeerFlow
Overview
Open-source super agent harness by ByteDance for long-horizon research, coding, and creation with sub-agents, memory, sandboxes, and skills.
DeerFlow, from ByteDance, is an open-source long-horizon super agent harness for tasks such as research, coding, and content creation. The GitHub repository describes DeerFlow as orchestrating sub-agents, memory, sandboxes, tools, skills, and a message gateway to handle tasks that can take minutes to hours. DeerFlow 2.0 is a ground-up rewrite of the original Deep Research framework, with the earlier framework maintained on the 1.x branch. The project is distributed on GitHub under the MIT license.
Product overview
Capabilities, pricing and fit
DeerFlow is best understood as an agent-development framework. An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.
Information as of July 30, 2026
What it can do
- Agent application development
An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.[1]
Autonomy level
80/100
Our subjective rating of how independently the product carries out its documented tasks, considering the human setup, input, approval and review it needs. This is not a measured success rate.
Comparisons
Custom Comparisons
Some of the use cases of DeerFlow:
- Building long-horizon autonomous workflows
- Coordinating sub-agents for complex tasks
- Research automation and deep exploration workflows
- Coding and software task automation
- Experimenting with memory, sandboxes, tools, and extensible skills
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Popularity level: 68%
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