Where does the browser automation code run?
An external worker, a hosted browser Function, a browser-local app action and a hosted agent are different execution models. The choice determines who deploys the code, starts the browser, records the result and stops the run.
A scheduled job should return a verified result and stop its owned browser even when an action fails. The scheduler's successful HTTP trigger is not proof that the browser completed the business operation.
Compare the execution model
Steel: The reviewed browser documentation establishes sessions, profiles and credentials. It does not establish a hosted Python handler with deployment and invocation APIs. An external worker can control a Steel browser; price and operate that worker separately.
Anchor Browser: Automation Tasks produce versioned workflows from a prompt or a recorded demonstration. Test and edit the workflow, then invoke it through the task API. Compare this authoring model with writing a handler directly.
Compare deployment ownership
Steel: Compare managed Steel with the documented self-hosted path explicitly. Self-hosting gives the team infrastructure responsibility that a hosted browser subscription would otherwise cover.
Anchor Browser: Use a browser session from existing code or deploy a reusable Automation Task. The task path includes workflow editing and versioning; direct CDP leaves execution ownership with your application.
Compare the evidence from a run
Steel: Steel documents live and past sessions as well as Agent Traces. Browser recordings answer what happened on the page; traces add context around the agent or application driving it.
Anchor Browser: Anchor documents MP4 session recordings and a live browser used during demonstrations. Keep the session artifact alongside the task's version, inputs and completion result.
How to evaluate this choice
Keep an external runner when you already operate one and need portability. A native execution layer can remove deployment work; browser-local code can reduce repeated network calls. Compare actual workload behavior before assuming either always wins.
- Confirm the supported language, entry point and dependency packaging.
- Trace deployment, version selection, invocation and cancellation.
- Keep the handler runtime limit separate from browser session duration.
- Decide whether scheduling is native or supplied by another service.
- Associate results and logs with both the code version and browser session.
Requirements side by side
| Requirement | Steel | Anchor Browser |
|---|---|---|
| Code execution | External worker | Automation Tasks |
| Scheduled execution | External scheduler | Task execution path |
| Recordings / replay | Documented | Documented |
Sources: docs.steel.dev [1] ↗docs.steel.dev [2] ↗docs.steel.dev [3] ↗docs.steel.dev [4] ↗docs.steel.dev [5] ↗docs.steel.dev [6] ↗docs.anchorbrowser.io [7] ↗docs.anchorbrowser.io [8] ↗docs.anchorbrowser.io [9] ↗docs.anchorbrowser.io [10] ↗docs.anchorbrowser.io [11] ↗docs.anchorbrowser.io [12] ↗
Which approach fits?
Choose Steel when you want browser infrastructure that can fit a self-hosted deployment, with profiles and credentials available through browser-focused APIs.
Steel tradeoff: Hosted and self-hosted Steel are different operating choices. A cloud feature's documentation does not establish identical packaging, retention or operational support in a self-hosted installation.
Choose Anchor Browser when you want managed sign-in and an automation task you can demonstrate, edit and invoke from your application.
Anchor Browser tradeoff: A demonstrated automation task and an arbitrary Python handler are different authoring models. Evaluate how much control you need over the code, dependencies and exact workflow.
A useful acceptance check
Write a pass/fail result for the real task before running the evaluation. Record the account, configuration and code version next to that result. Repeat failures need an explanation, not an automatically different browser configuration.
When Notte belongs on this shortlist
Steel's managed and self-hosted choices make infrastructure ownership a concrete deciding factor. Keep that option on the shortlist when operating the browser is intentional; evaluate Notte when owning fewer execution and authentication components is the actual goal.
Anchor's demonstration or prompt-authored Automation Tasks and Notte's Python Functions suit different authoring preferences. Both document website-authentication tooling, so a credible recommendation must address the actual login and workflow-editing path.
Notte: Functions deploy Python code with a run() entry point. Invoke them over HTTP or with an SDK, inspect run history, and roll back code by redeploying an earlier version as the latest version.
Consider this third option when its documented mechanism addresses a requirement left open by the two providers above. A working configuration on either original provider can still be the better choice; compare the task and ownership cost before switching.
Sources: docs.steel.dev [1] ↗docs.anchorbrowser.io [2] ↗docs.notte.cc [3] ↗