--- title: "deer-flow vs agent-opt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bytedance-deer-flow-vs-future-agi-agent-opt" tools: ["bytedance-deer-flow", "future-agi-agent-opt"] --- # deer-flow vs agent-opt *GraphCanon updated Aug 16, 2026* ## Verdict Pick deer-flow if deer-flow is an advanced SuperAgent platform for handling complex tasks over extended periods with a comprehensive set of functionalities such as sandboxes and memories; pick agent-opt if agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies. [deer-flow](https://deerflow.tech) reports 80k GitHub stars, 11k forks, and 948 open issues, last pushed Aug 16, 2026. [agent-opt](https://app.futureagi.com) has 71 stars, 7 forks, and 0 open issues, last pushed Jun 30, 2026. Figures are from public GitHub metadata via [deer-flow's repository](https://github.com/bytedance/deer-flow) and [agent-opt's repository](https://github.com/future-agi/agent-opt). | | [deer-flow](/tools/bytedance-deer-flow.md) | [agent-opt](/tools/future-agi-agent-opt.md) | | --- | --- | --- | | Tagline | An open-source long-horizon SuperAgent that handles complex tasks over minutes to hours. | Open Source Library for Automated Optimization of AI Agent Workflows | | Stars | 80,066 | 71 | | Forks | 10,961 | 7 | | Open issues | 948 | 0 | | Language | Python | Python | | Adopt for | Deer-flow is an advanced SuperAgent platform for handling complex tasks over extended periods with a comprehensive set of functionalities such as sandboxes and memories. | Agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [deer-flow](/tools/bytedance-deer-flow.md) | [agent-opt](/tools/future-agi-agent-opt.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 35d | | Open issues (now) | 948 | 0 | | Stars delta | +2.9k (30d) | Unknown | | Open issues delta | -29 (30d) | Unknown | | Full report | [trust report](/tools/bytedance-deer-flow/trust.md) | [trust report](/tools/future-agi-agent-opt/trust.md) | ## Decision facts: deer-flow - **Adopt for:** Deer-flow is an advanced SuperAgent platform for handling complex tasks over extended periods with a comprehensive set of functionalities such as sandboxes and memories. ## Decision facts: agent-opt - **Adopt for:** Agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies. ## Choose when ### Choose deer-flow if… - License: deer-flow is MIT, agent-opt is Apache-2.0. - Tags unique to deer-flow: agentic-framework, langchain, multi-agent, python. - When you need to manage lengthy workflows over minutes to hours that require constant supervision or adaptation by the AI agent, deer-flow's long-horizon capabilities make it suitable. ### Choose agent-opt if… - License: agent-opt is Apache-2.0, deer-flow is MIT. - Tags unique to agent-opt: aioptimization, automation, cicd, evaluation. - Also covers Evaluation & Observability. - - When your project needs seamless CI/CD integration alongside automated optimization ## When NOT to use deer-flow - For short, straightforward tasks that do not require extensive workflows (under a minute), deer-flow might be overkill due to its advanced functionalities and setup complexity. - If your team is primarily working with technologies like Node.js or TypeScript rather than Python, other tools might offer better integration and support. ## When NOT to use agent-opt - - If your project does not require Python or if it cannot meet the specific requirement of having Python ≥ 3.10 - - In scenarios where CI/CD integration is not a priority for your AI workflow optimization ## Common questions ### What is the difference between deer-flow and agent-opt? deer-flow: An open-source long-horizon SuperAgent that handles complex tasks over minutes to hours.. agent-opt: Open Source Library for Automated Optimization of AI Agent Workflows. See the comparison table for live GitHub stats and shared categories. ### When should I choose deer-flow over agent-opt? Choose deer-flow over agent-opt when License: deer-flow is MIT, agent-opt is Apache-2.0; Tags unique to deer-flow: agentic-framework, langchain, multi-agent, python; When you need to manage lengthy workflows over minutes to hours that require constant supervision or adaptation by the AI agent, deer-flow's long-horizon capabilities make it suitable. ### When should I choose agent-opt over deer-flow? Choose agent-opt over deer-flow when License: agent-opt is Apache-2.0, deer-flow is MIT; Tags unique to agent-opt: aioptimization, automation, cicd, evaluation; Also covers Evaluation & Observability; - When your project needs seamless CI/CD integration alongside automated optimization. ### When should I avoid deer-flow? For short, straightforward tasks that do not require extensive workflows (under a minute), deer-flow might be overkill due to its advanced functionalities and setup complexity. If your team is primarily working with technologies like Node.js or TypeScript rather than Python, other tools might offer better integration and support. ### When should I avoid agent-opt? - If your project does not require Python or if it cannot meet the specific requirement of having Python ≥ 3.10 - In scenarios where CI/CD integration is not a priority for your AI workflow optimization ### Is deer-flow or agent-opt more popular on GitHub? deer-flow has more GitHub stars (80,066 vs 71). Stars measure visibility, not whether either tool fits your constraints. ### Are deer-flow and agent-opt open source? Yes - both are open-source projects on GitHub (deer-flow: MIT, agent-opt: Apache-2.0). ### Where can I find alternatives to deer-flow or agent-opt? GraphCanon lists graph-backed alternatives at [deer-flow alternatives](/tools/bytedance-deer-flow/alternatives) and [agent-opt alternatives](/tools/future-agi-agent-opt/alternatives) ([deer-flow markdown twin](/tools/bytedance-deer-flow/alternatives.md), [agent-opt markdown twin](/tools/future-agi-agent-opt/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/bytedance-deer-flow-vs-future-agi-agent-opt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, deer-flow or agent-opt? deer-flow: Very active. agent-opt: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for deer-flow and agent-opt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [deer-flow trust report](/tools/bytedance-deer-flow/trust); [agent-opt trust report](/tools/future-agi-agent-opt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=bytedance-deer-flow`](/api/graphcanon/graph?tool=bytedance-deer-flow) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_