Firebase, Statsig, and PostHog are the best A/B testing tools for mobile apps if you want to start without a massive budget. Optimizely and LaunchDarkly lead for enterprise teams. But the right pick depends on your app’s traffic, your team’s technical skill, and (honestly) how much you’re willing to spend.
The mobile testing market went through a blender in 2025. OpenAI bought Statsig’s team. Taplytics shut down entirely. Three other tools changed owners. Half the “best tools” lists out there recommend products that no longer exist as standalone tools. This list is current as of June 2026, with real pricing that most roundups conveniently leave out.
If you’re looking for a step-by-step guide on how to run mobile tests, that’s a different post. Check our guide to mobile app A/B testing. This one answers a simpler question: which tool should you pick?
Best A/B testing tools for mobile apps at a glance
| Tool | Best for | Starting price | Free tier? | iOS + Android | Stats engine |
|---|---|---|---|---|---|
| Firebase | Free option | $0 forever | Yes (unlimited) | Both + Flutter, Unity | Frequentist |
| Statsig | Statistical rigor | $150/mo (Pro) | Yes (2M events/mo) | Both + Flutter, Unity | Frequentist + Bayesian |
| PostHog | Open-source all-in-one | $0.0001/request | Yes (1M requests/mo) | Both + Flutter | Frequentist |
| GrowthBook | Data warehouse teams | $40/seat/mo (Pro) | Yes (3 users) | Both + Flutter | Frequentist + Bayesian |
| LaunchDarkly | Feature flags first | $0 (Dev plan) | Yes | Both + Flutter | Frequentist |
| Amplitude | Product analytics users | $49/mo (Plus) | Partial (no tests on free) | Both + Flutter | Frequentist |
| Optimizely | Enterprise | ~$36K/year | No (trial only) | Both + Flutter | Frequentist |
| VWO | Marketing teams | ~$1K/mo | No (trial only) | Both + Flutter | Bayesian |
Every tool on this list works on both iOS and Android. Every one supports at least React Native or Flutter. The differences are in pricing, statistical methods, and how much setup your developers will curse you for.
For the broader A/B testing software market (including web tools), we have a separate buyer’s guide. And if you want the general best A/B testing tools list that includes web-only options, that’s over there.
1. Firebase A/B testing: best free option
Price: Free. No catch. It sits on top of Remote Config and Firebase Analytics, both of which are also free.
SDKs: iOS, Android, React Native, Flutter, Unity.
Firebase is what most teams start with because it costs nothing and integrates with tools they already use. You can change what people see in your app without pushing an update to the app store. Google calls this Remote Config.
That alone solves the biggest headache in mobile testing: waiting days for Apple or Google to approve your update just to test a new onboarding screen.
Firebase added web support in March 2026, so it’s no longer mobile-only. But mobile is still where it shines.
The catches. Firebase updates your test results once a day, not in real time. It has no variance reduction (a way to get reliable results faster with less traffic). The segmentation is basic.
And if you’re building a subscription app, Firebase can’t track what happens when the app is closed. Trial-to-paid conversions, renewals, cancellations? Invisible. Dealbreaker for paywall testing.
Best for: Teams already in the Google ecosystem with straightforward testing needs and no budget for paid tools.
2. Statsig: best statistical engine (but read the fine print)
Price: Free tier gives you 2M events/month (generous). Pro is $150/month plus $0.05 per additional 1,000 events above 5M.
SDKs: iOS (Swift), Android (Kotlin), React Native, Flutter, Unity. Local evaluation runs in under a millisecond after setup.
Statsig bundles feature flags, A/B testing, product analytics, and session replay in one platform. For mobile teams, the local evaluation speed matters. Your app doesn’t wait on a network request to decide which version to show.
That keeps your app fast, which matters more than most people realize. A testing tool that adds 200ms to your app’s startup time is quietly hurting every test you run.
The elephant in the room. OpenAI acquired the Statsig team in September 2025 for roughly $1.1 billion. They wanted the engineers, not the product. In May 2026, Amplitude took over the Statsig brand and customers. The people who built Statsig are now building things at OpenAI. Amplitude inherited the code but not the builders.
The product still works. The free tier is still one of the best in the category. But if you’re picking a tool for the next two years, this ownership situation is worth watching.
Best for: Teams who want strong statistics at an affordable price and are comfortable with some uncertainty about the product’s direction.
3. PostHog: best open-source all-in-one
Price: 1M feature flag requests/month free (tests use the same quota, no separate charge). Above that, $0.0001 per request, stepping down at volume.
SDKs: iOS (Swift), Android (Kotlin), React Native, Flutter. Automatically tracks taps and screen views. Offline event queuing built in.
PostHog’s pitch is simple: stop paying for five different tools. Analytics, session replay, feature flags, A/B testing, and surveys all live in one product. For mobile teams, the offline queuing is a nice touch. Your app stores events locally when there’s no connection and syncs them later.
The pricing model is unusually transparent. You’re paying for flag evaluations, period. No per-person pricing that punishes growth. No experimentation add-on that doubles the bill. More than 90% of PostHog’s customers reportedly use it entirely free.
The catches. Statistical rigor trails dedicated platforms. No CUPED (a method to reduce noise in your test results and get answers faster). No sequential testing on basic plans. Enterprise features like SSO and audit logs require paid tiers.
Best for: Developer-leaning teams who want one tool for everything and value pricing transparency.
4. GrowthBook: best for data warehouse teams
Price: Free cloud tier (3 users, 1M events/month). Pro is $40/seat/month. Self-hosted is free with no limits (open source).
SDKs: iOS (Swift), Android (Kotlin/Java), Flutter, React Native (via JavaScript SDK).
GrowthBook connects directly to your data warehouse (Snowflake, BigQuery, Redshift). Your test metrics get computed on your own data, not a copy sitting in someone else’s system. For teams that already have a data warehouse, this is a big deal. You don’t have to set up duplicate tracking or wonder if the numbers match.
The pricing model is seat-based, not usage-based. Whether your app has 10,000 or 10 million monthly people, the cost stays the same. That’s rare. Most tools punish you for growing.
The Pro tier packs real statistical muscle. CUPED reduces noise so you get answers faster. Sequential testing lets you check results early without inflating your error rate. And multi-arm bandits automatically send more traffic to the winning version. GrowthBook also supports Bayesian A/B testing if that’s your preference.
Best for: Teams with a data warehouse who want full control over their test data and don’t want pricing that scales with app traffic.
5. LaunchDarkly: best feature flag platform with experiments
Price: Developer plan is free forever (unlimited flags, 10M logs, A/B testing included). Foundation plan starts at $10/service connection/month plus $8.33 per 1,000 monthly active people. The experimentation add-on costs roughly $3 per 1,000 monthly active people on top of that.
SDKs: iOS (v9+), Android (v9+), React Native (v10, Expo-compatible), Flutter (v4+). Also supports watchOS, tvOS, and macOS.
Most roundups skip this: on mobile, feature flags matter more than the testing itself. Feature flags let you turn features on or off for specific people without an app update.
If a test goes badly on a website, you redeploy in five minutes. If a test goes badly in a mobile app, you’re waiting for an app store review. Feature flags let you kill a bad version instantly.
LaunchDarkly was built for exactly that. It’s the industry standard for feature flag reliability, with native targeting by OS version and app version. You can target “everyone on iOS 17 or newer” using version rules without building manual lists.
The catches. Experimentation is a paid add-on. The free Developer plan includes basic A/B testing, but the Foundation and Enterprise plans charge separately for experiments. Many buyers get surprised by the final number.
Our take: If your team already uses feature flags for releases, just add experiments to that same tool. If you’re starting from scratch and only want A/B testing, LaunchDarkly is overkill. Start with Firebase or PostHog.
Best for: Engineering teams where feature flags are the priority and experiments are a bonus.
6. Amplitude Experiment: best for product analytics teams
Price: Starter is free for up to 50K monthly tracked people (flags only, no tests). Plus starts at $49/month with 1 active test. Growth is custom pricing for full testing. A typical mid-market setup runs $40K-$70K/year.
SDKs: iOS, Android, React Native, Flutter. Deep integration with Amplitude Analytics.
Amplitude’s strength is that analytics and experiments share the same data. The user segments you built for analytics work as test audiences. The funnels you track become experiment goals. No CSV exports, no integration headaches.
The company also recently took over the Statsig platform (see the Statsig section above). How they manage two testing products at once is an open question.
The catches. The free tier has zero tests. You need at least the Plus tier for a single active test. Full A/B testing and testing multiple things at once require the Growth tier, which starts around $40K/year.
Best for: Teams already paying for Amplitude Analytics who want to add experiments without switching platforms.
7. Optimizely Feature Experimentation: best for enterprise
Price: Entry-level contracts start around $36K/year. Mid-market ($50K-$80K/year). Large enterprise ($200K+ /year). Annual contracts only. No free tier. 30-day trial.
SDKs: iOS (Swift/Obj-C), Android (Java/Kotlin), React Native, Flutter.
Optimizely has been doing this for over a decade. The platform supports both client-side and server-side testing, testing multiple variables at once, and full feature management. The statistical engine is mature. The customer success team actually knows what they’re talking about.
Their analysis of 127,000 tests found that only about 12% produce a confident winner. That’s a sobering number. Statistical rigor matters more than a pretty dashboard. If your tool can’t tell you when a result is noise, you’ll ship changes that don’t actually help.
The catches. The pricing puts it out of reach for most small and mid-size teams. You need a separate analytics tool. Implementation is complex enough that most companies bring in a partner or hire an A/B testing agency to set it up.
Best for: Enterprise teams with dedicated testing programs and a budget to match.
8. VWO mobile app testing: best for marketing teams
Price: Mobile app testing starts around $1,000/month for 10K monthly tracked people. This is a separate module from VWO’s web testing. Free tier was discontinued in late 2025. Trial only.
SDKs: iOS (~285KB), Android (~200KB), Flutter (wrapper), React Native. The SDKs are lightweight.
VWO is primarily a web testing tool that added mobile support. For marketing teams who already use VWO on their website, extending to mobile makes sense. The visual editor lets non-technical people set up tests without writing code.
VWO also uses Bayesian statistics, which is math that works with less traffic. Helpful for mobile apps where individual screens rarely get the visitor volumes a website homepage does.
For a deeper comparison, we’ll have a full VWO A/B testing deep dive covering both web and mobile.
The catches. Mobile testing is a separate paid module. If you’re paying for VWO web and VWO mobile, the bills stack up. The free tier is gone. And the tool isn’t mobile-native in its architecture. It was built for websites first.
Best for: Marketing teams who already use VWO for web testing and want to extend their setup to mobile.
How to choose the right tool
Forget feature matrices for a minute. This is the decision tree that actually matters for most mobile teams looking for the best A/B testing tool for iOS and Android:
Already using Firebase? Start there. It’s free and already integrated. You’ll outgrow it eventually, but it’s the fastest path to your first mobile test.
Developer team that wants one platform? PostHog or Statsig. Both have generous free tiers and bundle everything from flags to analytics.
Have a data warehouse? GrowthBook. Warehouse-native means your test data lives where the rest of your data lives.
Feature flags matter more than experiments? LaunchDarkly. The most reliable flag infrastructure in the category. Add experiments when you need them.
Already paying for Amplitude? Amplitude Experiment. Everything is already connected.
Enterprise budget and dedicated CRO team? Optimizely. Proven, mature, expensive.
Marketing team already using VWO? VWO Mobile. Extend what you have.
One thing every option on this list shares: they all use server-side evaluation to push changes without app store updates. That’s not a feature to look for. It’s a requirement. Any tool that forces you to submit a new app binary for every test variant isn’t a real mobile testing tool.
Our take: The industry is quietly moving away from “A/B testing tools” and toward feature flag platforms that happen to support experiments. For mobile, this makes sense. Rolling back a bad test version without an app store submission matters more than fancy statistics. Pick the tool that gets your releases under control first. The experimentation features will follow.
Ronny Kohavi, who ran testing at Microsoft and Airbnb, found that only 10 to 33% of A/B tests produce clear winners. The tool won’t change those odds. But a tool with strong statistics will at least tell you the truth about which tests moved the needle.
There’s another problem most roundups ignore. On Android, roughly 70% of active devices run a non-current OS version. Even on iOS, up to 18% of iPhones and 51% of iPads are behind.
If your test only ships in a new app binary, the people who haven’t updated never see it. Your “random sample” isn’t random at all. It’s skewed toward your most engaged, update-happy people. Server-side testing with feature flags avoids this entirely.
Testing your website and landing pages instead of a native app? Tools like Kirro handle that side. The ideal setup for most teams: a mobile tool like Statsig or Firebase for in-app tests, plus a web A/B testing tool for the pages that drive your installs.
For teams focused on improving app conversion rates, testing inside the app is only half the picture. Your app store listing conversion rate and your mobile app conversion benchmarks matter just as much. The right testing stack covers all three.
Notable tools that didn’t make the main list
Harness FME (formerly Split.io): Harness acquired Split.io in June 2024. Free plan available. Strong mobile SDKs handling 50B+ flag evaluations daily. The product is solid, but the positioning is still settling post-acquisition. Worth watching if you’re already in the Harness CI/CD ecosystem.
Airship (Apptimize): Airship bought Apptimize in 2019. It’s now part of their customer engagement platform. Best for testing push notifications and in-app messaging. Not a general-purpose A/B testing tool anymore.
CleverTap (Leanplum): CleverTap absorbed Leanplum in 2022. Starts at $999/month. Full engagement suite with A/B testing as a feature, not the focus. If you need a CRM that also does testing, it works. If you need testing that also does everything else, look elsewhere.
Taplytics: Gone. The original Taplytics product was fully decommissioned. The team pivoted to DevCycle, which Dynatrace then acquired in January 2026. If any “best tools” list still recommends Taplytics, it’s outdated.
Google Optimize: Also gone. Shut down in September 2023. It was web-only anyway, but many lists still mention it.
FAQ
What is A/B testing for mobile apps?
It’s showing two versions of something inside your app to different groups of people, then measuring which performs better. A screen, a feature, a pricing page. The mechanics are different from web testing because you can’t just inject a script. You need an SDK (a code library your developers add to the app) and server-side testing. That way you can change things without waiting for an app store review. Our full mobile app A/B testing guide covers the how-to in detail.
Which tool is best for mobile application testing?
Firebase is the most widely used free option. For paid tools, Statsig and PostHog offer the best value with generous free tiers. The comparison table at the top breaks down all eight tools by pricing, SDKs, and statistical methods. If you need a broader comparison including web-only tools, check our best A/B testing tools roundup.
Can you A/B test a mobile app without pushing an app update?
Yes. All eight tools on this list use server-side evaluation combined with feature flags to change what people see without submitting a new app version. This is the whole point of dedicated mobile testing tools. Your app checks a server on launch (or uses a cached configuration) to decide which version to show. No app store review needed.
Is Firebase A/B testing enough for most apps?
For basic tests (which onboarding flow converts better, which button color gets more taps), Firebase is plenty. It’s free, reliable, and already integrated if you use Firebase for anything else. You’ll want to upgrade when you need real-time results, advanced segmentation, variance reduction to speed up tests, or subscription lifecycle tracking. At that point, Statsig or PostHog are the natural next step.
How is this list different from web A/B testing tools?
Every tool here has native mobile SDKs for iOS and Android. Web testing tools inject JavaScript into a browser page, which doesn’t work inside a native app. Mobile tools use SDKs (code libraries) and server-side evaluation instead. If you’re testing a website or landing pages, the general A/B testing software roundup is more relevant. For your website’s split tests, Kirro’s visual editor lets you change headlines and CTAs without code. Set up a free test and see results within days.
Do mobile A/B testing tools work with split testing software?
Split testing and A/B testing are the same thing (different names, same concept). Every tool on this list supports it. The mobile-specific difference is that split tests run through feature flags and SDKs rather than URL redirects. For a comparison of Optimizely and its alternatives, we have a separate breakdown.
Randy Wattilete
CRO expert and founder with nearly a decade running conversion experiments for companies from early-stage startups to global brands. Built programs for Nestlé, felyx, and Storytel. Founder of Kirro (A/B testing).
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