Good question — choosing an “antidetect” (fingerprint-masking / multi-profile) browser depends mostly on what you need it to do and the legal/ethical constraints you must follow. Below is a compact, practical decision guide you can use to pick and test candidates.

1. Clarify your real use-case (this determines the required features)

• Account management / social media / marketplace sellers: need strong profile isolation, persistent cookies, reliable proxy integration, browser automation API, team sharing.
• Ad/affiliate work or A/B testing: need consistent and repeatable fingerprinting, timezone/locale control, and ability to emulate many device types.
• Web scraping & automation: need headless/stable automation support, stealth against bot detectors, request throttling, rotating fingerprints.
• Privacy/anonymity: need robust anti-fingerprinting, WebRTC/IP leak protection, minimal telemetry, local control of data.
• QA / compatibility testing: multiple browser engine emulations, reproducible profiles, logging.

2. Must-have technical features

• Profile isolation: separate storage for cookies, localStorage, extensions and cache.
• Fingerprint control: change user agent, screen size, timezone, language, fonts, audio/video/canvas, WebGL, platform strings.
• Proxy support: per-profile proxies (HTTP/SOCKS/SSH/MTProto) and proxy health checks.
• WebRTC leak protection and IP masking.
• Extension management and custom extensions support (if you need them).
• Automation API or integration with tools you already use (Selenium, Puppeteer, Playwright, APIs).
• Export/import profiles and team/shared profiles if working in a team.
• Persistent and non-persistent profiles (ephemeral sessions).
• Local vs cloud operation: whether profiles run on your machine (less vendor trust) or vendor cloud (easier scale).
• Logging & audit: session logs, login history, and error traces.

3. Important quality, security, and operational factors

• Reliability: frequent updates and active maintenance against new anti-fraud detectors.
• Performance: low memory/CPU overhead when running many profiles.
• Security practices: encryption of stored profiles, 2FA for the management console, audited privacy policy.
• Data ownership: where are profiles stored? Can vendor access them?
• Compliance & legal: Does your intended use comply with laws and terms of service of the websites you interact with? (Don’t use for fraud, bypassing paid protections, or illegal activity.)
• Support & docs: onboarding guides, API docs, responsive support.
• Cost model: per-profile, per-seat, per-concurrent-session — estimate your monthly cost given expected scale.

4. Practical evaluation checklist (test these before buying)

• Create 3–5 representative profiles for your use-case.
• Run fingerprint and leak tests (browserleaks.com, amiunique.org, ipinfo checks) to confirm:
  • No WebRTC/IP leak
  • Canvas/WebGL/Audio fingerprints change as expected
  • Timezone/locale/font changes show correctly
• Integrate one profile with your automation tool (Selenium/Puppeteer) and run a scripted login + action.
• Test proxy switching and stability under load.
• Measure memory/CPU per profile and estimate host capacity.
• Test profile export/import, backup, and deletion behavior.
• Try vendor support: open a ticket, time how fast/helpful they are.
• Check legal/security docs and whether the vendor responds transparently about data storage.

5. How to weigh choices (sample quick scoring)

• Core feature fit (40%): profile isolation, fingerprinting control, proxy support, automation APIs.
• Security & data control (20%): encryption, local storage option, vendor access.
• Reliability & updates (15%): frequency of updates and track record vs anti-fraud tech.
• Performance & scalability (10%): resource usage and cloud/local scaling options.
• Cost & support (15%): price fits budget, good documentation and responsive support.

Rate each candidate 1–5 in each area, multiply by weight, and pick the highest-scoring product that meets legal/ethical requirements.

6. Red flags to avoid

• Vendors promising “100% detection-proof” or “bypass all fraud systems” — unrealistic.
• Closed-source clients that run everything in vendor cloud without clear data handling.
• No option to run locally if you need to control data.
• Very cheap unlimited profiles or per-profile prices that are too good to be true.
• Lack of automation API or no documentation.

7. Legal & ethical guidance (must-read)

• Antidetect tooling can be used for legitimate tasks (privacy, testing, account management), but also for policy-violating or illegal activity. Make sure your use-case complies with website terms of service, contract obligations, and laws (fraud, circumvention, data theft).
• Keep logs for legitimate auditing and avoid automating actions that would harm others (spam, scraping paid content, creating fraudulent accounts).

8. Quick recommendation flow you can follow right now

1. Write down your primary use-case and number of concurrent profiles.
2. Require these absolute features: per-profile proxies, WebRTC leak protection, automation API, profile isolation.
3. Shortlist 3 vendors that meet those requirements.
4. Run the practical evaluation checklist for each (fingerprint tests, automation test, proxy stress test).
5. Score them with the weighting above and choose the best fit.
6. Start with a small paid plan or trial and scale after you validate reliability in production.

If you tell me your specific use-case (e.g., “managing 50 Amazon seller accounts from one machine,” or “privacy-first browsing for personal use”), I can map that to the exact feature priorities and give a short checklist tailored to you.