Statsig vs PostHog - Which Should You Pick in 2026?

Statsig and PostHog get compared constantly because they solve overlapping problems the same cheap way - both bundle feature flags, experiments and product analytics into one platform, and both keep flags close to free. The difference is which one is the center of gravity. Statsig is experimentation-first. PostHog is analytics-first. That single distinction decides most of it.

I’ve read both tool pages. Here’s the honest, use-case comparison, with GrowthBook named as the open-source, warehouse-native third option.

The short version

Tool	Pricing model	Self-host / OSS	Best for
Statsig	Flags free, billed on analytics events; Pro $150/mo flat	No (SDKs open source)	Serious experimentation, free flag checks
PostHog	Flags free to 1M req/mo, then per request; each product bills separately	No (self-host unsupported)	Analytics, experiments and flags in one place
GrowthBook	$0 self-hosted, or $40/seat/mo cloud	Yes (MIT)	Warehouse-native experimentation, open source

The one-line version - Statsig if experimentation is the point, PostHog if analytics is. The rest is the nuance.

Where Statsig wins

Statsig is an experimentation platform first and a flag tool second. It was built by ex-Facebook engineers to recreate Facebook’s internal experimentation stack, and the A/B testing engine is the real center of gravity, not the flags - a full statistical engine with sequential testing and CUPED variance reduction. It’s the strongest experimentation engine in this comparison.

The billing model is the pitch. Flag and config checks are unlimited and free on every tier, because Statsig monetizes analytics and experiment events instead. You can evaluate flags a billion times a month at zero cost. The free Developer tier is genuinely generous - 2M analytics events, 50,000 session replays, no credit card - and Pro is a flat $150/mo (5M events included, then $0.05 per 1,000), which is a rare predictable number in this category. There are 30+ SDKs.

Two gotchas. First, the meter moves on events - heavy product-analytics usage is where the bill lives, even though flags are free, and Pro is one project per subscription. Second, and bigger - OpenAI acquired Statsig on 2 September 2025 for a reported ~$1.1 billion, and founder Vijaye Raji became OpenAI’s CTO of Applications. The product still ships independently, but adopting it today is a multi-year bet on a roadmap that now sits inside OpenAI.

Where PostHog wins

PostHog is a product-analytics suite - events, funnels, session replay, surveys - with feature flags and experiments built in as one product line among many. Its experiments read directly from your product analytics, so the metrics you test against are the same events you already track. That tight coupling is the whole point, and it’s an advantage standalone flag tools can’t match. On experimentation depth it lands second only to Statsig here. Flags are cheap - the first 1,000,000 requests a month are free, then fractions of a cent, tiered down to $0.000010 per request past 50M - and experiments draw from that same meter and free tier. It was founded in 2020 out of Y Combinator’s S20 batch, and a Series E in October 2025 put it at a reported $1.4 billion valuation.

Two gotchas. First, it’s open source under MIT, but self-hosting is officially unsupported - no guarantees, no tagged releases, you assume the risk - so don’t buy it as an enterprise self-host path. Second, each product bills separately, so your flags line can stay cheap while analytics, replay and surveys climb the total. Model every product you plan to turn on, not just flags. The steep learning curve is also its most common complaint.

Where GrowthBook fits

If experimentation is the real need and you want it open source and on your own data, GrowthBook is the third option. It’s MIT-licensed and warehouse-native - it queries the BigQuery, Snowflake or Databricks warehouse you already run rather than ingesting a copy of your events - and the stats engine is the real thing: CUPED, sequential testing, Bayesian analysis, multi-arm bandits, SRM checks. The self-hosted OSS edition runs unlimited users for $0, and Cloud Pro is $40 per seat per month.

The gotcha is dependency and difficulty. GrowthBook needs a properly instrumented warehouse to deliver its value, and the statistics have a genuine learning curve. Reviews cite an engineer-first UI and thorough-but-hard-to-navigate docs.

Statsig vs PostHog - which should you pick?

• Experimentation is a first-class, statistical need - Statsig. Its engine is the strongest here, and free flag checks make the flag half essentially free. Price the OpenAI-ownership asterisk in.
• You want analytics, experiments and flags in one data model - PostHog. Experiments reading straight from your product metrics is a genuine practical win, and one platform beats stitching several together.
• Pure flag usage is mostly what you have - Statsig, because it never bills flag evaluations at all. PostHog is cheap too, but Statsig’s model is the cheaper of the two at high flag volume.
• You send huge volumes of analytics events - watch both. That’s where Statsig’s bill lives, and PostHog’s separate per-product meters can climb the same way. Model your event volume, not just flags.
• You want open source and experimentation on your own warehouse - neither Statsig nor PostHog offers a supported self-host. Go to GrowthBook.

The honest bottom line - pick by your center of gravity. If you’re running experiments as a core discipline and want the deepest stats engine with free flag checks, Statsig wins, provided you’re comfortable betting on a product now inside OpenAI. If your team lives in analytics - funnels, replay, events - and wants experiments and flags reading from the same data, PostHog is the stronger bundle. Both keep flags cheap, so the flag line rarely decides it. The experimentation-versus-analytics question does.

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Pricing verified against each vendor’s site on 26 July 2026. The Statsig OpenAI acquisition figure (~$1.1 billion, 2 September 2025) and PostHog’s reported $1.4B Series E valuation are from third-party reporting, attributed as such. Full detail on our Statsig, PostHog and GrowthBook reviews.