DeerFlow vs OWL

Side by side, as alternatives to Manus. Rows that differ are highlighted; the strongest value in a row is marked. Unknown means no source yet.

Also replaces Manus: + Openclaw + OpenManus + AgenticSeek + Skyvern + Kortix (formerly Suna)+ Nanobrowser

DeerFlowbytedance/deer-flow

OWLcamel-ai/owl

Manuspaid product

Cost and coverage

Price

$0 software; you run it

See pricing page source ↗

Autonomous web browsing

Partly

Yes

Deep research reports

Partly

Yes

File and code tasks in a sandbox

Partly

Yes

Slides generated from a prompt

Partly

Yes

Scheduled agent tasks

Partly

Yes

Connectors to your apps

Partly

Yes

Jobs covered

5 of 6 jobs

2 of 6 jobs

All 6

Popularity and activity (from GitHub)

Stars

84,212Top

20,151

—

Gain this week

Unknown

—

Signal

Building history

—

Commits / 4 wk

679Top

—

Latest release

v2.1.0 · 2026-09-24

Unknown

—

Commits / 12 wk

1,333

—

People committing / 12 mo

98+

—

Issues opened / closed, 30 days

359 / 335

1 / 0

—

Facts, with sources on each project page

Runs on my machine?Differs

Self-hosted with Docker (recommended) or a local dev setup

Yes, Python scripts or a local Gradio web UI; Docker image also available

Hosted by the vendor

Code licenceDiffers

MIT

Apache-2.0

—

Model weights licenceDiffers

No separate model weights; you bring model API keys or host a model yourself (vLLM supported)

No separate model weights; you bring your own model API key or a local Ollama model

—

Commercial useDiffers

Yes, MIT code; model and search provider terms apply separately

Yes, Apache-2.0 code; model terms depend on the provider you choose

—

Paid services needed?Differs

Needs a model (API key or self-hosted) and a web search provider such as Tavily or InfoQuest; self-hosted fetchers exist

An LLM API key is needed for the main examples; an Ollama example runs a local model; other tool keys are optional

Subscription

HardwareDiffers

Minimum 4 vCPU, 8 GB RAM, 20 GB free SSD for local use (more for Docker or shared servers); a local LLM is sized separately

Not documented; cloud model use needs only Python; browser tasks need a multimodal model

—

Operating systemsDiffers

Linux recommended for servers; macOS and Windows (Git Bash) for development or evaluation

Windows, macOS and Linux; Python 3.10 to 3.12

—

Setup effortDiffers

Medium; make setup writes config, then make docker-start; needs Docker Compose v2.24+ and model and search keys

Medium; pip/uv/conda install plus .env API keys, or a prebuilt Docker image

—

Stars over time

Switch to Growth % to compare projects of different sizes fairly.

DeerFlow
OWL

Focus a point, use arrow keys, or tap for its value.

Tracked daily since 16 Oct 2026. Dashed history: estimated from public records of when people starred the repo. Lines connect observations only; gaps contain no measured points.

Growth % starts at each project's first observed point in the shown range. Zero-star starts are unavailable.

Notes for a video or post

A plain summary with today's date and a link to the sources. Check each project page before you publish.

DeerFlow vs OWL (as alternatives to Manus)
Figures from RepoQuarry, 21 Oct 2026. Sources: https://repoquarry.dev/compare?ids=deer-flow,owl&product=manus

Manus: See pricing page
DeerFlow: free software; does 5 of 6 Manus jobs
OWL: free software; does 2 of 6 Manus jobs

- DeerFlow: 84,212 GitHub stars, 1,333 commits in 12 weeks, licence MIT
- OWL: 20,151 GitHub stars, 7 commits in 12 weeks, licence Apache-2.0

Where they differ:
- Runs on my machine?: DeerFlow Self-hosted with Docker (recommended) or a local dev setup; OWL Yes, Python scripts or a local Gradio web UI; Docker image also available
- Code licence: DeerFlow MIT; OWL Apache-2.0
- Model weights licence: DeerFlow No separate model weights; you bring model API keys or host a model yourself (vLLM supported); OWL No separate model weights; you bring your own model API key or a local Ollama model
- Commercial use: DeerFlow Yes, MIT code; model and search provider terms apply separately; OWL Yes, Apache-2.0 code; model terms depend on the provider you choose
- Paid services needed?: DeerFlow Needs a model (API key or self-hosted) and a web search provider such as Tavily or InfoQuest; self-hosted fetchers exist; OWL An LLM API key is needed for the main examples; an Ollama example runs a local model; other tool keys are optional
- Hardware: DeerFlow Minimum 4 vCPU, 8 GB RAM, 20 GB free SSD for local use (more for Docker or shared servers); a local LLM is sized separately; OWL Not documented; cloud model use needs only Python; browser tasks need a multimodal model
- Operating systems: DeerFlow Linux recommended for servers; macOS and Windows (Git Bash) for development or evaluation; OWL Windows, macOS and Linux; Python 3.10 to 3.12
- Setup effort: DeerFlow Medium; make setup writes config, then make docker-start; needs Docker Compose v2.24+ and model and search keys; OWL Medium; pip/uv/conda install plus .env API keys, or a prebuilt Docker image

Stars show popularity, not quality. Check each project page before publishing.

Want share images and a ready video description? Open a project's creator kit.

Numbers: GitHub, fetched nightly. Facts: read from each project's own documentation, with the source on its page. How we check. bytedance/deer-flow ↗camel-ai/owl ↗

DeerFlow vs OWL

Stars over time

Notes for a video or post

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