Best Free A/B Testing Tools in 2026 (Tested and Compared)

Search “free a/b testing tools” and most results are 14 or 30-day trials of paid products, not something that keeps working for free afterward. This guide separates the two: what is genuinely free forever in 2026 (GrowthBook’s open-source core, PostHog’s free tier, what is left of native experimentation in Google Analytics 4, Microsoft Clarity for qualitative research) from trials dressed up as “free,” including the real limits of each honest option and when the cost of keeping one running for free quietly outgrows the price of a paid tool. For a broader comparison across paid and free vendors side by side, see our neutral guide to CRO tools compared; this article stays focused on the free side of that same landscape.

Why most “free A/B testing tool” lists are trials in disguise

Open almost any “top 10 free A/B testing tools” roundup and the pattern repeats: nine of the ten entries are paid products with an evaluation period, listed as “free” because you technically do not pay in the first few days. That is not a lie, but it is also not what most people mean when they search for something free: they want a tool that keeps running after a month, with no card on file and no experiment left orphaned halfway through.

The test is simple, and worth running on any tool advertised as free before you install its snippet:

• Is there a visible expiration date at signup? If so, it is a trial, not a permanently free tool.
• Does signup ask for a card number before letting you use it? Genuinely free tools do not require this; a card request is the most reliable signal that automatic billing is scheduled for when the window ends.
• What happens to experiments already running once the window closes? On a genuinely free tool, nothing changes. On a trial, the experiment usually stops collecting data, or the results get locked behind a paywall.
• Does the company own the code, or can you audit and self-host it? Only an open-source tool guarantees that; any free proprietary product can change its terms at any time.

None of these questions are about distrusting a vendor on principle. They are about not planning your first experiment around a tool that will ask for a credit card right in the middle of it. Donnu, for the record, operates exactly like a trial: a free 14 days, no cost, but with a deadline, not a permanent free tier, and that is how we refer to it throughout this guide.

What is actually free forever in 2026

Once the disguised trials are set aside, only a small handful of options keep working with no deadline and no charge, each with a very different proposition. None of them is a fully managed, complete A/B testing platform for free at the same time: each trades something (your own hosting, a usage cap, or only partial coverage of what an A/B test needs) for zero cost.

• GrowthBook (open-source, self-hosted): feature flagging and experimentation under an open-core MIT license. The core is free forever, and you can inspect, modify, and host it yourself with no license fee. GrowthBook also sells a managed Cloud tier, including a Starter plan free for up to three users, plus a paid Cloud Pro plan at 40 dollars per seat per month (up to 50 users), for teams that would rather not run the infrastructure.
• PostHog (hosted free tier): a product analytics platform with experimentation built in. Its free tier includes 1 million events per month at no cost, hosted by PostHog itself (a separate self-host option also exists), with experiment evaluations drawn from the same feature-flag-request allowance. No credit card is required to sign up.
• Google Analytics 4 (limited native experimentation): GA4 is free and ubiquitous, but on its own it is not a dedicated A/B testing tool: it lets you compare audiences and segments without a built-in controlled experimentation engine (random assignment, significance calculation). Google Optimize, the tool that used to fill that role inside GA4, was discontinued on September 30, 2023. Since March 2026, however, Google’s Firebase A/B Testing, previously limited to mobile apps, has also covered websites, with random assignment and statistical significance, and it stays free on the Spark plan.
• Microsoft Clarity (free heatmaps and replay, no native A/B testing): a free heatmap and session-recording tool from Microsoft, with no paid tier at all. Excellent for generating a hypothesis (“visitors stop scrolling here, why?”), but it does not test whether a specific change improves conversion; that remains the job of a separate experimentation tool.
• Donnu (trial, not free forever): worth mentioning as an additional option, with the honest caveat that it does not belong in the same category as the four above. Donnu’s 14-day free trial gives full access to a client-side A/B testing platform with a Bayesian read, but it expires: once the window closes, it is a paid tool like any other on the broader comparison list.

Comparison table: what each option actually covers

Tool	What it covers	Real limit	Self-hosting required?
GrowthBook (open-source)	Feature flags plus client-side and server-side A/B testing	No usage limit imposed by the software; the ceiling is your own infrastructure’s capacity	Yes, you install, patch, and scale the database
PostHog (free tier)	Product analytics plus experiments, including A/B testing	1 million events per month at no cost; confirm the current allowance on PostHog’s own pricing page, it can change over time	No, hosted by PostHog (self-hosting is a separate option)
Google Analytics 4	Analytics and audience comparison	Not a dedicated A/B testing tool on its own since Google Optimize’s 2023 shutdown; since March 2026 Firebase A/B Testing (free) covers apps and websites	No, fully hosted by Google
Microsoft Clarity	Heatmaps and session recording	Free, no native A/B testing (useful for hypotheses, not for testing them)	No, hosted by Microsoft
VWO / Convert	Full A/B, multivariate, and personalization suites	No permanent free plan as of 2026; VWO offers a 30-day trial, Convert a 15 to 30-day trial, both convert to paid plans starting in the hundreds of dollars per month	No, fully hosted
Donnu (trial)	Client-side A/B testing with a Bayesian read	14-day trial, then converts to a paid plan; not free forever	No, hosted by Donnu

The real limits of each free option

A free tool is never free in the absolute sense: the cost just moves, out of the invoice and into your team’s time. Here is where each option collects that hidden price.

Option	What you give up or pay elsewhere	Who should think twice
GrowthBook self-hosted	No official SLA or guaranteed support; you apply patches, scale the database, and handle a 2am incident if it goes down	Teams with nobody dedicated to keeping infrastructure running
PostHog free tier	Hitting the monthly event ceiling typically means throttling or the need to upgrade to a paid plan; data retention can also be shorter than on a paid tier	Sites with traffic that regularly exceeds the free ceiling, making the real cost unpredictable
GA4 alone (without Firebase A/B Testing)	Delivers no random assignment or statistical significance calculation on its own; any comparison made with GA4 alone lacks the sample rigor covered in our guide to statistical significance	Anyone who needs to declare a winner with statistical confidence, not just eyeball a raw difference between segments
Microsoft Clarity	No A/B testing at all, only qualitative behavior (where the eye goes, where clicks land)	Anyone who already knows the hypothesis and needs to validate it with numbers, not just understand the behavior
VWO / Convert trial	Access ends or converts to a paid plan after the trial window; not a permanent no-cost option	Anyone looking for something free forever, never paying anything
Donnu trial	Access ends or converts to a paid plan after 14 days; not a permanent no-cost solution	Same as above

Notice that none of these rows are about the tool being bad. They are about what it deliberately leaves out of the free version, and whether that specific gap breaks your use case or not.

When it is worth moving from free to paid

The right question is not “is free good enough?” in the abstract, it is “does my engineering time keeping this running already cost more than a comparable paid alternative’s monthly fee?” For a self-hosted tool like GrowthBook, that tipping point usually arrives earlier than teams expect, because maintenance cost does not grow linearly, it grows in steps, each one triggered by a specific event.

The most common triggers that push a team from free to paid:

• Traffic volume starts to demand database scaling that nobody on the team knows how to operate under pressure, and every incident turns into a firefighting sprint.
• More than one person or team depends on the tool, and a bad late-night update now takes down other teams’ experiments too, not just yours.
• You need to isolate data across brands, clients, or business units, an architecture requirement that free self-hosting usually does not solve out of the box, demanding extra engineering on top of the standard install.
• The monthly “engineering hours spent maintaining this” tally starts to exceed a paid competitor’s fee for the same feature coverage.

None of these conditions alone is an automatic reason to switch. The most reliable signal is when two or three of them show up together, at which point the real cost of “free” has already passed what you would pay for a managed tool with support included.

Which free tool fits your use case

The right free tool depends less on features and more on how much traffic and engineering capacity you actually have right now.

Use case	What matters most	Best-fitting free option
Pre-revenue startup	Zero cost, minimal setup time, no infrastructure to babysit	PostHog’s free tier (no self-hosting) or Firebase A/B Testing if already on GA4/Firebase
Product validating PMF	Enough event volume to actually reach significance, some tolerance for engineering effort if data residency matters	GrowthBook self-hosted if the team already has engineering capacity, otherwise PostHog’s free tier
Side project or personal site	Lowest possible traffic, no budget, no team to maintain infrastructure	PostHog’s free tier or Microsoft Clarity paired with GA4/Firebase for the hypothesis-plus-test loop

None of these are permanent choices. A side project that turns into a funded product, or a PMF-stage product whose traffic outgrows a free ceiling, is exactly the case the previous section describes: the moment to reassess is when the maintenance cost or the usage cap becomes the actual bottleneck, not before.

Before running your first test, check if your free tool can handle the volume you need

A free tier based on an event or visitor cap is only a problem if your test actually needs more volume than it covers. Before choosing between self-hosting and a hosted free tier, calculate how many visitors your specific test requires: if the number sits comfortably below a free ceiling like PostHog’s, the usage limit stops being a relevant factor in the decision.

Current conversion rate%Minimum detectable effectrelative (%)absolute (pp)Confidence909599%Power8090%Visitors per week (total)Testtwo-sidedone-sided

-Visitors per variation

-Total (2 variations)

-Estimated duration

Two-proportion normal approximation, 2 variations (50/50). Tweak the inputs and watch it update live.

If the calculator’s result shows a large sample, cross-check that number against the monthly ceiling published by whichever free tool you are evaluating before installing the snippet. For the full walkthrough of calculating sample size and reading the result with rigor, see our complete guide to A/B testing.

Checklist: what to verify before trusting a free tool with your first test

None of these checks depend on paying anything. It is ten minutes of work before installing any snippet, paid or free:

• Does the tool calculate sample size automatically, or leave that entirely up to you? Without that calculation, it is easy to declare a winner with too few visitors, a mistake covered in detail in our guide to statistical significance.
• Does it show a p-value or an honest Bayesian probability, without hiding the sample size behind the result? A “winner” with no context on how many people generated that number is not trustworthy.
• Does it check for SRM (Sample Ratio Mismatch)? If a 50/50 traffic split arrives skewed, something broke in collection, and no result from that test is worth trusting, no matter how clean it looks.
• Is the statistical rigor explained anywhere, not just the final result? If you cannot follow where the number came from, you also will not be able to defend the decision to the rest of the team.
• How is data isolated if you run tests for more than one brand, site, or client on the same account? A data leak between properties is the kind of mistake that only surfaces far too late.
• What happens to a running test if you hit the free limit mid-month? Confirm whether collection stops, degrades, or only blocks the report, before that happens in the middle of an important test.

A free tool that answers these six questions well is a solid choice for your first test. One that answers none of them, even if it costs nothing, can end up costing more in a wrong decision than any monthly fee would.

Automate This in Donnu

Keeping a free tool running has a cost that never shows up on an invoice: your own time, fixing SRM by hand, scaling a database at 2am, or relearning GA4’s dashboard every time Google redesigns the interface. If your team does not have that engineering capacity to spare, or if you have already felt that cost firsthand, it is worth considering a ready-made tool with statistical rigor built in instead of one assembled piece by piece.

Donnu is not free forever, and we do not pretend it is: it is a free 14-day trial of a paid, client-side tool with a Bayesian read and per-account data isolation from day one, with nothing to self-host. If your situation calls for something genuinely free forever, the honest options in this guide (GrowthBook, PostHog, GA4 plus Firebase A/B Testing, Clarity) remain the right starting point, but if what you want is to stop maintaining infrastructure and get back to focusing on the test itself, start the trial and compare it directly against what you use today.

Read also: GrowthBook vs Statsig: open-source versus managed testing | CRO tools compared: a neutral guide by category

Leia em português: Ferramenta de teste A/B grátis, o que é real em 2026.

References

• GrowthBook. Predictable pricing, free tiers, enterprise plans. growthbook.io/pricing.
• PostHog. Pricing, including the free tier allowances. posthog.com/pricing.
• Google. Analytics Help Center, including the Google Optimize sunset notice. support.google.com/analytics.
• Firebase. Firebase A/B Testing is now available for the web. firebase.blog/posts/2026/03/ab-testing-for-web.
• Microsoft Clarity. Free heatmap and session recording tool. clarity.microsoft.com.
• VWO. Pricing and trial details. vwo.com/pricing.