5 款最佳免费开源 A/B 测试工具

Also known as split testing or multivariate testing, A/B testing is the practice of splitting your audience to test variations of a product design, new feature, call to action, landing page – anything you can imagine, really.

There are dozens of A/B testing tools available, but what they offer varies widely. Many lean toward marketing use cases (i.e. testing website landing pages) and aren't useful for product feature testing, or only support specific platforms like Shopify or WordPress.

In this guide, we're looking at the best free and open-source A/B testing tools. Open-source tools are mainly built for developers, so we recommend marketers read our guide to the best alternatives to VWO.

A good open-source A/B testing tool lets you experiment with changes to your product and measure their impact on real users without locking you into a proprietary platform. Most solid tools include:

• A/B and multivariate testing for comparing different variations
• Statistical analysis to determine when results are significant
• Feature flags for safely rolling out changes to specific user segments
• SDKs for your stack (JavaScript, Python, React, mobile, etc.)
• Self-hosting options so you keep full control of your data

More advanced tools go further with:

• Bayesian and Frequentist statistics so you can choose the approach that fits your team's workflow
• Multi-armed bandit experiments that automatically allocate traffic to the winning variation
• Holdout groups to measure the long-term cumulative impact of your experiments
• Visual editors for creating variations without code changes
• Warehouse-native architecture that connects directly to your existing data infrastructure
• Product analytics integration so you can analyze experiment results alongside broader user behavior

Here's how the most popular open-source A/B testing tools compare:

1. PostHog

PostHog is an all-in-one developer platform that integrates a comprehensive A/B testing suite with many other tools, such as Product Analytics, Feature Flags, Session Replay, Error Tracking, and more. It's designed for product-minded engineers, growth teams, and product managers who need to move fast and iterate based on reliable, actionable insights.

PostHog’s experimentation suite supports multivariate experiments, and targeting by geography, user cohorts, and person properties – all of which is built atop PostHog's multivariate feature flags. PostHog supports both Bayesian and Frequentist statistical approaches, so you can choose the method that fits your team's workflow.

Who is PostHog for?

PostHog is ideal for product teams and engineers, particularly those who don't want to assemble a complicated stack of analytics tools. As an all-in-one platform, PostHog includes everything a team needs to measure user behavior, test new features, and roll them out. It's also one of the best open-source session replay tools available.

Features and benefits

• A/B and multivariate testing
• Unlimited experiments
• Multivariate feature flags
• Bayesian and Frequentist statistics engines
• Full product analytics suite
• Ability to select segments for experiments
• Event pipelines for integration with data warehouses
• Traffic visualization with user path analysis

How much does PostHog cost?

Experiments are billed under feature flag requests, which are free up to 1 million requests per month alongside 1 million analytics events and 5,000 session recordings. After the free monthly allowance, you'll pay $0.0001/request, and requests cost progressively less the more you use. You can set billing limits to ensure you don't get surprise bills.

While PostHog is open source, its A/B testing features aren't included in the open source release – you'll need the free cloud tier to access them.

Bottom line

For teams looking for all the tools they need to experiment and improve their products, PostHog is a great choice. This is especially true for startups and scaleups thanks to its generous free tier.

Further reading: New to A/B testing? Read a software engineer's guide to A/B testing and our guide to common A/B testing mistakes. Looking for mobile testing tools? See our guide to the best mobile app A/B testing tools.

GrowthBook is an open-source platform for feature flags and A/B tests that helps teams to deploy code efficiently and analyze experiments. Built by engineers who wanted better insights on new releases, it is a modular solution that promotes feature flagging as an essential step in the development process. This means it can be used as a full-stack platform, a plugin feature flagging tool, or an analysis engine.

Who is GrowthBook for?

GrowthBook is built for data, engineering, and product teams who need the power of a customizable platform without having to build it in house.

Features and benefits

• Warehouse-native architecture – connects directly to BigQuery, Redshift, Snowplow, and more
• Both Bayesian and Frequentist statistics engines with CUPED variance reduction
• Visual A/B test editor for no-code experiments (Pro plan)
• Multi-arm bandits and safe rollouts (Pro plan)
• Lightweight SDKs for speed
• Easy to implement – no need for data or engineering resources
• Self-hosted and managed options available

How much does GrowthBook cost?

GrowthBook open source (MIT license) is free and includes unlimited experiments. Their cloud Starter plan is free for up to 3 users with unlimited experiments. The Pro cloud plan costs $40 per user per month and adds advanced statistics (CUPED, sequential testing), a visual A/B test editor, and multi-arm bandits.

Bottom line

GrowthBook is the best choice for data and engineering teams that already have a data warehouse and want to run experiments on top of their existing infrastructure. Its warehouse-native approach means you never have to send raw user data to a third party.

Unleash is a feature management platform that provides an overview of all features across your applications and services. The platform empowers engineering teams to implement A/B tests via feature toggles and offers accurate user targeting. It's particularly popular with privacy-conscious organizations since it doesn't require you to share user data with third parties.

You can use Unleash to define the rules of your experiments, but the platform doesn’t provide all the tools you need to manage A/B tests end-to-end. Instead, you'll need to connect your experiment with an analytics platform like PostHog, Google Analytics or Mixpanel in order to visualize results.

Who is Unleash for?

Unleash is for autonomous development teams who want a lightweight way to test, validate, and rollout new features safely.

Features and benefits

• Accurate user targeting
• Fast toggle evaluation, so performance issues are spotted fast
• Extensive APIs
• 25+ official SDKs covering all major languages and frameworks
• Privacy-first architecture (no user PII leaves your infrastructure)
• Integrations with Jira, Datadog, Microsoft Teams, and Slack
• Self-hosted and managed service available

How much does Unleash cost?

Unleash's open source self-hosted plan is free with unlimited feature flags and experiments. A self-service Enterprise plan starts at $75 per seat per month with a 5-seat minimum, available as cloud-hosted or self-hosted. Custom Enterprise pricing is available for teams that want annual contracts and dedicated support.

Bottom line

Unleash is the best open-source option for teams that primarily need feature flag management and want to add basic A/B testing on top.

Mojito is an open source split testing stack that lets you build, launch, and analyze experiments via Git/CI. The stripped-down tool consists of three modular components – a front-end library for bucketing users and tracking them, data models and events for fast reporting, and reporting templates and functions, so you can build your own visualizations for experiment analysis.

It's worth noting that Mojito is maintained by a small consultancy and has a slower development cadence than the other tools on this list. That said, its simplicity is part of the appeal – it's a lightweight, dependency-free option for teams that want full source control over their testing stack.

Who is Mojito for?

Mojito is a fully source-controlled stack for developers and technical product teams who want a simple solution with unlimited customization.

Strengths

• Simple APIs and unlimited customization
• No need for 3rd party analytics
• ~5kb front-end library for minimal page load impact
• Error tracking and handling
• No account required – deploy from your own infrastructure
• Lightweight solution for optimized page load speed

How much does Mojito cost?

Mojito is completely free and open source, and you don’t need an account to get started. It's distributed under a BSD 3-clause license.

Flagsmith is an open-source feature flag and remote configuration service that lets you manage features across mobile, web and server-side applications. You can use Flagsmith’s multivariate flags as a bucketing engine to place users into testing buckets and control the specific user experience that is being tested. Flagsmith doesn’t provide analytics for multivariate tests, however, so you’ll need to use a third-party provider to receive the stream of event data derived from the behavior of the user.

Who is Flagsmith for?

Flagsmith is targeted at data-driven front end and user experience teams who want to increase efficiency in their feature development.

Features and benefits

• Manage flags across multiple platforms
• Powerful segmenting rules
• Integrations with a number of popular analytics platforms
• Remote configuration allows you to toggle features without changing code
• On-premises hosting for maximum infrastructure control
• Integrations with Amplitude, Heap, Mixpanel, and more for analytics

How much does Flagsmith cost?

Flagsmith is open source and available on a BSD 3-clause license. It can be hosted entirely on-premises with pricing available on request. Their cloud free plan includes up to 50,000 requests per month for 1 team member with unlimited flags, environments, and segments. The Start-Up cloud plan is $45 per month for up to 1 million requests.

• Want an all-in-one platform that integrates A/B testing with product analytics, session replays, feature flags, and more? Go with PostHog.
• Already have a data warehouse and want to run experiments on top of your existing data? Choose GrowthBook.
• Primarily need feature flag management with basic A/B testing and a privacy-first architecture? Unleash is your best bet.
• Need open-source feature flags with remote configuration and on-premises hosting? Try Flagsmith.
• Want a minimalist, fully source-controlled split testing stack with zero vendor dependencies? Mojito is for you.

Is PostHog right for you?

Here's the (short) sales pitch.

We're biased, obviously, but we think you'll love PostHog if:

• You value transparency (we're open source and open core)
• You want tools to ship, track, and analyze new features – like A/B testing, feature flags, and session replays
• You want try before you buy (we're self-serve with a generous free tier)

It's completely free to get started – no credit card required. Our setup wizard handles configuration in minutes, or you can check out our docs to do it yourself.

What is the best free A/B testing tool?

It depends on what you need.

PostHog is the best option for product teams that want experimentation alongside product analytics, session replay, and feature flags in one platform – its free tier includes 1 million feature flag requests per month.

GrowthBook is the best choice for teams that already have a data warehouse and want a dedicated, warehouse-native experimentation tool – it's completely free to self-host with no limits. If you're looking for more options beyond open source, check out our guide to the best mobile app A/B testing tools.

What's the difference between feature flags and A/B testing?

Feature flags let you toggle features on or off for specific users without deploying new code. A/B testing uses feature flags to randomly split users into groups (variants) and then measures which variant performs better against a goal metric.

In practice, most A/B testing tools on this list – PostHog, GrowthBook, Unleash, Flagsmith – are built on top of a feature flagging engine. The distinction matters because tools like Unleash and Flagsmith are primarily feature flag tools that can be used for A/B testing, while PostHog and GrowthBook provide end-to-end experimentation with built-in statistical analysis.

Is GrowthBook really free?

Yes, with caveats. GrowthBook's self-hosted open-source version (MIT license) is genuinely free with unlimited users, experiments, and feature flags. The cloud-hosted Starter plan is free for up to 3 users. If you need advanced features like CUPED variance reduction, a visual editor, or multi-arm bandits, you'll need the Pro plan at $40/user/month.

Can you do A/B testing without code?

Some tools on this list offer visual editors that let you set up web experiments without writing code. GrowthBook includes a visual A/B test editor on its Pro plan. For fully no-code A/B testing, you'll likely want a marketing-focused tool like VWO or Optimizely instead, though these are neither free nor open source.

You can also use a combination of an AI agent and MCP to help you do this.

Do I need a separate analytics tool with open-source A/B testing?

It depends on the tool. PostHog includes full product analytics alongside experimentation, so you don't need anything else. GrowthBook is warehouse-native and pulls experiment results from your existing data warehouse, so you'll need an analytics pipeline already in place. Unleash and Flagsmith are primarily feature flag tools – you'll need a separate analytics platform (like PostHog, Google Analytics, or Mixpanel) to analyze your experiment results. Mojito includes its own reporting templates but requires you to set up a data storage layer.

What's the difference between Bayesian and Frequentist A/B testing?

These are two statistical approaches for analyzing experiment results.

• Frequentist testing uses p-values and confidence intervals – you define a sample size upfront, run the test, and check if results are statistically significant at the end.

• Bayesian testing calculates the probability that one variant is better than another and updates continuously as data comes in, making it easier to interpret mid-experiment.

PostHog and GrowthBook support both approaches. Most other open-source tools on this list don't include built-in statistical analysis at all – you'll need to calculate significance yourself or use a separate tool.

Can I self-host an A/B testing tool?

Yes – that's one of the main advantages of open-source A/B testing tools. GrowthBook offer both cloud and self-hosted options with full experimentation features. Unleash and Flagsmith can be self-hosted for free with their open-source editions. Mojito is self-hosted only. Self-hosting gives you complete control over your data, which is particularly important for teams with strict privacy requirements or regulatory compliance needs.

• The best mobile app A/B testing tools
• A software engineer's guide to A/B testing
• Common A/B testing mistakes
• The best open-source feature flag tools
• PostHog vs. GrowthBook

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