PostHog Experiments Pricing, Decoded - Why "Free A/B Testing" Has a Second Meter (2026)

Search “PostHog experiments pricing” and you’ll mostly find the marketing line - flags are free for the first million requests, so experiments are basically free too. That’s half true, and the missing half is where teams get surprised.

PostHog experiments don’t have their own price. They run on the feature-flag meter, and there’s a second meter you can’t see from the experiments page. This is a neutral decode of how the model actually works, a worked example of what an experiment really costs, and where two other tools price experiments more cheaply.

What PostHog bills experiments on

Start with the thing PostHog does not charge separately for - experiments. There’s no experiment plan, no per-test fee. When you run an A/B test, the variant assignment is a feature-flag evaluation, and experiments draw from the same flag request meter and the same 1M free requests.

Here’s the flag meter in full:

Monthly flag requests	Price per request
First 1,000,000	Free
1M to 2M	$0.0001
2M to 10M	$0.000045
10M to 50M	$0.000025
50M+	$0.000010

There’s no base fee for the flags line. For the assignment side of an experiment, this is genuinely cheap. A million variant assignments a month cost nothing.

The part the experiments page won’t tell you: the second meter

An experiment isn’t just assigning users to a variant. It’s measuring what those users do. The metrics you test against are product-analytics events, and analytics is a separate PostHog product with its own meter.

That’s the trap. PostHog’s whole architecture is that each product - flags, analytics, session replay, surveys - meters and bills separately. Flags might stay inside the free million. But the conversion events, funnels and exposures your experiment is scored on are analytics events, on the analytics meter, with a different free allowance. Your flags line can read “free” while your analytics line quietly climbs.

This is also PostHog’s genuine strength, to be fair - its experiments read directly from your product analytics, so the metric you test against is the same event you already track, with no piping data between two tools. The tight coupling is the reason to pick PostHog. Just know that the coupling means an experiment touches two meters, not one.

A worked estimate

Say you run experiments on a product doing 5 million flag requests a month.

1. Flag/assignment side. First 1M free. The next 1M (1M to 2M) at $0.0001 is $100. The next 3M (2M to 10M band) at $0.000045 is $135. So the assignment side is about $235/mo. Cheap.
2. Analytics side. Every exposure and conversion event your experiments measure is an analytics event on a separate meter with its own free tier. If you’re a lightly instrumented team, this may stay free. If you already run PostHog analytics across the product, the experiment events pile onto a bill you’re paying anyway - and that meter, not flags, is where the number moves.

The honest read - the assignment side is close to free, and the analytics side is the real cost. If you’re already an analytics-led team on PostHog, the experiments are a fantastic add-on because the events are already flowing. If you’re adopting PostHog mainly to run experiments, budget for the analytics meter, because that’s the one you’ll actually feel.

One more line to remember - the open-source MIT build exists, but PostHog’s self-hosting is officially unsupported, with no guarantees and no tagged releases. Don’t treat self-host as a way to dodge the meters. Full detail on the PostHog review.

Cheaper ways to run experiments

If the analytics meter is what worries you, two tools attack experiment cost from different angles.

Statsig - if you want flag checks to be free and a flat price. Statsig’s model is the mirror image of PostHog’s - flag and config checks are unlimited and free on every tier, and you pay only on analytics events. The free Developer tier includes 2M events, unlimited flag checks and 50,000 session replays with no credit card. Pro is a flat $150/mo (5M events included, then $0.05 per 1,000). Its experimentation engine, built by ex-Facebook engineers with sequential testing and CUPED, is the strongest in this set. The asterisk - OpenAI acquired Statsig in September 2025, so adopting it is a multi-year bet on a roadmap that now sits inside OpenAI. Not a dealbreaker, a thing to price in.

GrowthBook - if you have a warehouse and want no per-event meter at all. GrowthBook is warehouse-native - it queries the BigQuery, Snowflake or Databricks warehouse you already run instead of ingesting a copy of your events. That means there’s no analytics meter to inflate, because your event data never leaves your infrastructure. The stats engine is the real thing - CUPED, sequential testing, Bayesian, multi-arm bandits, SRM checks. Cloud Starter is $0 for 3 users, Cloud Pro is $40 per seat per month up to 50 users, and the self-hosted MIT build runs unlimited users for $0. The gotcha - it needs a properly instrumented warehouse and someone who understands the statistics, or you get a fraction of the value.

So which one?

• Already an analytics-led team on PostHog Cloud - run experiments in PostHog. The events are already flowing, the integration is genuinely the best part, and the assignment side is close to free. Just don’t read “flags are free” as “experiments are free” - the analytics meter is the real one.
• You want flag checks free and a budget you can predict - Statsig, with the OpenAI-ownership asterisk factored in.
• You already run a data warehouse and have someone who owns the stats - GrowthBook removes the per-event meter entirely, and the self-hosted build is free.

For a wider view, see our best experimentation platforms roundup and the head-to-head Statsig vs GrowthBook breakdown.

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Pricing verified against each vendor’s site on 26 July 2026. Feature-flag and experiment pricing changes often - we re-verify regularly. The Statsig OpenAI acquisition figure is from third-party reporting and attributed as such.