Steel and Browserbase both provide remote browser infrastructure for automation and agent workflows. This page focuses on the differences that typically matter in production: deployment surface, observability defaults, and cost model.

Both platforms work with standard automation tooling and cover the common “cloud browser” requirements. The choice usually comes down to how much control you need over the browser layer and how you want to operate, debug, and budget for sessions at scale.

At a glance

Common ground

• Remote browser sessions compatible with Playwright/Puppeteer/Selenium-style workflows.

• Persistent state primitives for reuse across sessions (for example, profiles/contexts).

• Stealth/proxy/CAPTCHA options available as part of the platform story.

Differences that matter

• Open-source runtime, transparency and self-hosting surface area

• Session lifecycle performance (benchmarkable via an open harness)

• Recording/replay and debugging defaults

• Packaging and plan boundaries (usage units and included quotas)

Summary

Differences that matter

1) Deployment surface

Steel

• The core browser runtime is open source and can be self-hosted and transparently inspected.

• Steel also offers a fully managed platform and enterprise offering.

• Self-hosting docs cover common deployment paths (for example, Docker).

Browserbase

• Browserbase is primarily a managed platform.

• Deployment options and controls are expressed through plan and enterprise offerings.

2) State and isolation

Steel

• Profiles are the durable unit for cross-session state (auth, cookies, browser configuration).

• Useful when workflows need consistent identity and repeatable reuse.

Browserbase

• Context-style state persistence supports reuse across sessions.

• Useful when you want a clean default session model and explicit reuse when needed.

3) Performance and reliability

• Performance: Steel is faster in the published lifecycle benchmark. See the open, reproducible harness (which includes Browserbase in the provider set) for current results and rerun it in your own region and workload: https://github.com/steel-dev/browserbench

4) Observability and debugging

Steel

• Live viewing and session recordings support fast failure diagnosis.

• Logs and traces are designed around quick iteration on flaky web workflows.

Browserbase

• Browserbase emphasizes session inspection and recording/replay tooling.

• Debugging experience depends on plan features and defaults.

5) Pricing model

Steel

• Billing unit: tiered plans with included usage.

• Typical fit: teams that want predictable monthly spend and straightforward capacity planning.

Browserbase

• Billing unit: tiered plans with included quotas across browser hours, bandwidth, and features.

• Typical fit: teams that want a managed platform where usage and feature access track plan levels.

When Steel is a good fit

• You want an open, inspectable browser runtime with a clear self-hosting path.

• You want a vendor-neutral browser API that works with standard automation tooling.

• You want agent-oriented SDKs and integrations to reduce glue code.

• You want predictable spend and simple capacity planning.

• You want reproducible benchmarking you can rerun in your own region.

Next step

• Start with Steel: steel-docs

• Reproduce lifecycle benchmarks: steel-browserbench

• Self-host Steel Browser: steel-self-host