The 5 Best AI Billing Platforms (February 2026)

The best AI billing platforms in 2026 are Lava (best for real-time enforcement with an AI gateway), Stripe (best for general-purpose payments), Orb (best for complex enterprise billing), Metronome (best for high-volume metering), Autumn (best for developer-first simplicity), and Flowglad (best for early-stage AI startups). The key differentiator is real-time enforcement: whether the platform can actually block a request when a user's credits run out, not just track that it happened.

Key Takeaways

• Real-time enforcement is the most important feature for AI billing. Tracking usage after the fact means you eat costs when users exceed their limits
• Lava is the only platform that combines an AI gateway with billing, so metering happens automatically at the proxy layer
• Stripe handles payments but not metering, margin calculation, or prepaid wallets. You will need to build those yourself
• Orb and Metronome are powerful for enterprise billing but add complexity that most early-stage AI startups do not need
• Prepaid wallets are becoming the default billing pattern for AI products because they eliminate the risk of users running up unpayable bills

If you are building an AI product that charges users based on usage, you need billing infrastructure that actually understands AI workloads. Flat-rate subscription tools were not designed for token-based pricing, real-time metering, or the prepaid wallet patterns that AI companies rely on. The billing platform you choose will shape your pricing flexibility, your margins, and how much engineering time you spend on infrastructure instead of product.

Here is what matters most and what most teams miss: how enforcement actually works. Every billing platform can track usage. Very few can actually stop a request before it happens when a user runs out of credits. That distinction will cost you real money at scale.

What Is AI Billing?

AI billing is the process of metering, rating, and collecting payment for AI usage, typically measured in tokens, API calls, or compute units, where costs are variable and scale directly with consumption.

Platform Comparison

Lava

Lava is purpose-built for AI platforms that resell AI capabilities to their end users. Unlike every other tool on this list, Lava was designed from day one for the B2B2C model: you are a platform, your users consume AI, and you need to meter, bill, and collect from those users in real time.

The core architecture is a prepaid wallet system. Your end users load funds through a hosted checkout that you embed in your app. As they consume AI, Lava meters the usage, applies your markup, and deducts from the user's balance in real time. You can send usage events directly through the API, just like you would with any other billing platform on this list. But if you route your AI requests through the Lava Gateway, metering becomes automatic. The gateway proxies requests to 600+ models across 30+ AI providers, counts tokens, calculates costs, and deducts from the wallet as a single atomic operation. No separate instrumentation. No separate billing pipeline.

That gateway integration is where Lava pulls ahead on enforcement. With every other platform on this list, you write balance-check logic before every request, handle concurrent race conditions, process enforcement webhooks, and maintain that code as your product evolves. With the Lava Gateway, the balance check and the request forwarding are a single atomic operation. If a user is out of credits, the request is rejected before it ever reaches the AI provider. No race conditions, no webhook delays, no enforcement code to write or maintain. Without the gateway, you can still use Lava's real-time balance checks before each request, similar to Autumn's /check pattern but backed by Lava's ledger.

Best for: AI platforms and SaaS products that need to charge end users for AI usage with minimal engineering overhead. Especially strong for products using multiple AI providers.

Pricing: Usage-based. No platform fees. The gateway is free.

Stripe Billing

Stripe Billing is the default choice for SaaS billing, and for good reason. It handles subscriptions, invoicing, payment collection, tax calculation, and revenue recovery at massive scale. With the completed acquisition of Metronome in January 2026, Stripe now has native usage-based billing capabilities that go well beyond its original meter API.

Stripe supports usage metering with up to 100M events per month included, and it has added credit-based features that let customers prepay and draw down balances. The Metronome integration brings enterprise-grade commit contracts, prepaid credits with drawdown, and multi-dimensional metering. For general SaaS with a usage component, this is a strong and getting-stronger option.

The limitation for AI products is twofold. First, Stripe does not know what a token is. It does not proxy AI requests or automatically meter API calls. You build the instrumentation layer that counts tokens, calculates costs per model, and sends usage events to Stripe. Second, Stripe processes meter events asynchronously with timestamps truncated to 15-minute windows. Even if you check a credit balance before making a request, the balance may be stale. There is a race condition window where users can exceed their credits between your balance check and when Stripe processes the event. Enforcement is your responsibility, and it is eventually consistent.

Best for: SaaS companies that already use Stripe and want to add usage-based components without switching payment processors.

Pricing: 0.7% of billing volume for the unified Billing plan. Payment processing fees (2.9% + $0.30) are separate.

Orb

Orb is a developer-focused billing platform built around real-time event ingestion and flexible pricing models. It processes billions of events per day using streaming aggregation, which means your usage data is available for queries and billing calculations as soon as it arrives. No batch processing, no overnight jobs.

Where Orb shines is pricing model flexibility. You can combine usage-based pricing, fixed fees, and per-seat charges in a single plan. You can define billable metrics by querying raw events with custom aggregation logic. You can simulate pricing changes before shipping them. Orb also supports prepaid credits with real-time drawdown, which is a meaningful step up from Stripe's credit model.

The enforcement model is "you call us, then you enforce." You query Orb for a customer's credit balance, Orb returns the current state, and your application decides whether to allow or deny the request. After the request, you send a usage event to Orb. This is faster than Stripe's async model, but it is still a check-then-act pattern. Orb never sees the actual AI request, so it cannot block anything. Miss an instrumentation point in your code, and the usage goes unmetered.

Best for: Developer tools and B2B SaaS companies with complex, hybrid pricing models that need real-time event processing and pricing experimentation.

Pricing: Custom, based on billing volume and event count. Platform fees apply on Advanced and Enterprise tiers.

Metronome (Now Part of Stripe)

Metronome was the leading standalone usage-based billing platform before Stripe acquired it for a reported $1B. It powered billing for OpenAI, Anthropic, and NVIDIA. As of January 2026, Metronome is part of Stripe's product suite.

Metronome's strength was always enterprise commit contracts: prepaid credits, minimum spends, postpaid overages, and hierarchical account structures. These are the billing patterns that large AI companies need when selling to enterprise buyers. If your sales team is closing six-figure annual contracts with committed spend and overage pricing, Metronome (now via Stripe) handles that complexity natively.

For enforcement, Metronome uses a webhook alert model. You configure spend thresholds, and when a customer's credit balance hits zero, Metronome sends a webhook to your application. Your application must then disable the customer's access. The documentation is explicit about this: your system must cut off platform access when it receives the webhook. The enforcement latency is event ingestion plus alert evaluation plus webhook delivery plus your application processing the webhook. That can be seconds to minutes, during which the customer continues making requests.

Best for: Enterprise SaaS companies with complex commit contracts and high-volume metering needs, especially those already on Stripe.

Pricing: Now part of Stripe Billing. Contact Stripe for current pricing.

Autumn

Autumn is an open-source billing layer that sits on top of Stripe and handles credits, usage limits, feature entitlements, and add-ons. The pitch is speed: three functions to integrate, no webhooks, and you have billing working in an afternoon. It is a YC-backed seed-stage company that has gained traction with early-stage AI startups.

Autumn is the closest competitor to real-time enforcement on this list. Its /check endpoint is designed to be called synchronously before granting access. If the customer has credits remaining, /check returns "allowed." If not, your app denies the request. This is meaningfully better than Stripe's async model or Metronome's webhook model.

The limitation is that Autumn is still a sidecar. Your application must call /check before every action. If a code path bypasses the check, there is no enforcement. There is also a race condition: between /check returning "allowed" and /track recording the usage, another concurrent request can also pass /check and both proceed. At high concurrency, this means systematic overage leakage. And Autumn does not meter AI requests, track token costs, or proxy to AI providers. It is a faster way to wire up Stripe billing, not purpose-built AI billing infrastructure.

Best for: Early-stage AI startups that want to ship billing fast on top of Stripe without building a full billing integration from scratch.

Pricing: Free until $8K monthly revenue. Startup plan at $375/month after that.

Flowglad

Flowglad is an open-source, webhook-free payments platform built for developers. Where Stripe requires you to manage webhook handlers for payment state changes, Flowglad exposes billing state directly through SDK methods. You call getBilling() on the backend or useBilling() in React, and you get the current state without maintaining webhook infrastructure.

The platform supports subscriptions, usage-based metering, credits, coupons, and hybrid pricing models. It uses a double-entry ledger internally, and the checkout experience is clean and embedded. For developers who want a payments integration that AI coding tools can implement in a single pass, Flowglad is designed for that workflow.

For enforcement, Flowglad follows the same check-before-acting pattern as Autumn. You call checkFeatureAccess() or checkUsageCredits() before processing a request. If the customer has credits, you proceed. If not, you deny. Same race condition risk, same developer burden of instrumenting every code path. Flowglad does not sit in the request path, so it cannot physically intercept requests.

Best for: Developers who want a clean, webhook-free payments SDK with good AI coding tool support.

Pricing: Free up to $1K/month billing volume. 0.65% of revenue after that. Stripe processing fees (2.9% + $0.30) on top.

How to Choose

The right platform depends on who you are billing and how your AI costs flow.

If you are billing end users (B2B2C): Your users are consumers inside your app. They do not want invoices or commit contracts. They want a balance, a simple top-up flow, and transparency into what they are spending. This is Lava's core use case. You can use Lava Monetize standalone with your own metering, or pair it with the Lava Gateway to eliminate the enforcement layer from your engineering backlog entirely. No balance checks, no webhooks, no race conditions.

If you are billing businesses (B2B) with simple usage pricing: Stripe Billing with its new Metronome-powered metering is the safe choice. You already have Stripe for payments. Adding usage-based billing on top is incremental, not a rearchitecture.

If you are billing enterprises with complex contracts: Stripe (with Metronome) or Orb handle commit contracts, prepaid credits, tiered pricing, and custom invoicing. These platforms are built for the sales-led motion where each customer has a unique deal structure.

If you need billing shipped fast on a budget: Autumn or Flowglad get you from zero to billing in an afternoon. Good for validating pricing early on, but you will outgrow them once you need real-time enforcement at scale, gateway integration, or end-user wallets.

For a deeper look at the pricing models themselves, see our guides on credit-based pricing for AI, usage-based billing for AI products, and how to bill end users for AI.

What You Are Actually Building

Whichever platform you choose, it helps to understand the full scope of usage-based billing for AI. There are four systems that every AI billing stack needs, and each platform on this list covers a different subset of them.

Metering. Capturing every API call with token counts, model, provider, and user attribution. This is the event ingestion pipeline. With Lava's gateway, this is automatic. With every other platform, you build the instrumentation yourself.

Rating. Converting raw usage into dollars. GPT-4o costs different amounts than Claude Sonnet. Prices change when providers update their rates. You need versioned price tables, markup calculations, and margin tracking. Orb and Metronome excel here for complex B2B pricing. Lava handles this automatically for prepaid models.

Collection. Actually getting paid. Prepaid wallets, credit card on file, invoicing, dunning, retry logic, refunds, PCI compliance. Stripe is the gold standard for payment processing. Lava and Flowglad both offer hosted checkout. Orb and Metronome leave payment collection to Stripe.

Visibility. Giving your customers real-time usage dashboards so they see what they are being charged for. Lava includes customer-facing wallet dashboards. Orb has a customer portal. Most other platforms leave this to you.

Building these four systems from scratch takes months of focused engineering. Most teams underestimate this because the first version feels straightforward. The metering pipeline works, the Stripe integration charges cards, the dashboard shows usage. Then you ship it, and the real work starts.

• A customer disputes a charge and you need chargeback handling
• You add a new product line and need a second pricing model running alongside the first
• A provider changes their rates and your margin calculations are wrong until someone notices
• You introduce a free trial and need to convert trial users to paid without losing usage data
• A customer's card expires and you need dunning, retry logic, and graceful degradation
• You want to change your pricing and need to migrate existing customers without breaking their experience
• Tax rules change and you need to handle collection in new jurisdictions
• An edge case in concurrent requests causes double-charging and you spend a week reconciling the ledger

That is not a one-time build cost. It is a permanent line item on your engineering capacity. Teams that build billing themselves report spending significant portions of every quarter on maintenance: patching edge cases, reconciling ledgers, updating pricing logic, handling failed payments, and adapting to new requirements. Every new product line, every pricing experiment, every compliance change runs through your billing code. The system never stops needing attention.

The platform you choose determines how much of this you own versus offload. The less of it you build, the more time you spend on product instead of infrastructure.

How Lava Helps

Lava exists because none of the general-purpose billing platforms solve the full problem for AI platforms that charge end users.

Lava Monetize gives you prepaid wallets, hosted checkout, real-time balance tracking, automatic top-ups, spending controls, and usage dashboards for your end users. Your users fund their wallet, use AI features, and see exactly where their money goes. You set the markup and see your margins on every request. You can send usage events to Lava directly through the API, just like any billing platform.

Where Lava goes further is the optional Lava Gateway, which routes AI requests to 600+ models across 30+ providers through a single API integration. When you use the gateway, every request is automatically metered at the proxy layer. Token counts, costs, and user attribution happen without you writing instrumentation code. Swap models or providers without touching your billing. And because the gateway and billing layer are connected, enforcement is automatic. No balance-check middleware. No webhook handlers. No race condition patches. That is an entire category of engineering work that disappears from your backlog.

Payments is historically difficult, detail-oriented work. It is not just about building it once. It is about maintaining it forever: reconciling ledgers, handling payment failures, managing refunds, staying PCI compliant, and adapting to new edge cases every month. That ongoing burden is best left to a company that specializes in payments, not bolted onto your engineering team's backlog. You build the product. Lava handles the money.