Comparison
deer-flow vs agent-opt
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.
Markdown twin · deer-flow alternatives · agent-opt alternatives
GraphCanon updated 5d
vs
Trust & integrity
| Signal | deer-flow | agent-opt |
|---|---|---|
| Maintenance | Very active (0d since push) As of 5d · github_public_v1 | Steady (35d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 5d · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- 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
Stars
- deer-flow
- 80k
- agent-opt
- 71
Forks
- deer-flow
- 11k
- agent-opt
- 7
Open issues
- deer-flow
- 948
- agent-opt
- 0
Language
- deer-flow
- Python
- agent-opt
- Python
Adopt for
- deer-flow
- 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
- 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
- deer-flow
- -
- agent-opt
- -
Runtime
- deer-flow
- -
- agent-opt
- -
License
- deer-flow
- MIT
- agent-opt
- Apache-2.0
Last pushed
- deer-flow
- Aug 16, 2026
- agent-opt
- Jun 30, 2026
Categories
- deer-flow
- AI Agents
- agent-opt
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- deer-flow
- Very active (96%)
- agent-opt
- Steady (60%)
Days since push
- deer-flow
- 0d
- agent-opt
- 35d
Open issues (now)
- deer-flow
- 948
- agent-opt
- 0
Stars delta
- deer-flow
- +2.9k (30d)
- agent-opt
- Unknown
Open issues delta
- deer-flow
- -29 (30d)
- agent-opt
- Unknown
Full report
- deer-flow
- Trust report
- agent-opt
- Trust report
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.
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.
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 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
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (bytedance/deer-flow) · observed Aug 16, 2026
- GitHub forks (bytedance/deer-flow) · observed Aug 16, 2026
- Last push (bytedance/deer-flow) · observed Aug 16, 2026
- License file (MIT) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (future-agi/agent-opt) · observed Aug 4, 2026
- GitHub forks (future-agi/agent-opt) · observed Aug 4, 2026
- Last push (future-agi/agent-opt) · observed Jun 30, 2026
- License file (Apache-2.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: deer-flow 80k · agent-opt 71 (synced Aug 16, 2026).
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 and agent-opt alternatives (deer-flow markdown twin, agent-opt markdown twin), 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 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; agent-opt trust report.