In 2026 just like before - the default advice for AI billing goes like this: pick a metering layer, plug it into Stripe for payments and you're done done. This made sense in 2024 but as of 2026 it's incomplete.

Stripe acquired Metronome for ~$1B in January 2026. That means the "standard stack" of Metronome + Stripe is now just Stripe. Orb only integrates with Stripe. Amberflo is primarily Stripe. If you followed the consensus advice, your entire billing infrastructure now depends on one payments company's roadmap.

Meanwhile, AI billing got harder. Credits became the dominant pricing mechanism. Hybrid models (subscription + usage + enterprise contracts) became the norm, not the exception. And the question changed from "can we meter tokens?" to "is this customer profitable?".

Here's what really makes the difference when choosing AI billing infrastructure in 2026.

But first…

Why the old criteria are wrong

Most comparisons rank billing platforms on metering throughput: events per second, ingestion speed, real-time aggregation. Those metrics matter, but they're table stakes. Every serious billing platform handles metering now.

The criteria that actually determine whether your billing system works at $3M, $10M, and $50M ARR are different:

The best AI billing systems, ranked by what matters

Tier 1: Built for AI billing complexity

These platforms were designed for the specific problems AI companies face: credits, tokens, hybrid pricing, and margin visibility.

Solvimon

Built by Kim Verkooij (ex-VP Product, Adyen) and Etienne Gerts (ex-SVP Technology, Adyen), who built and operated Adyen's internal billing engine at €970B+ in annual payment volume.

Why it ranks here: Solvimon treats credits and tokens as first-class financial primitives. Credit wallets carry full ledger logic (rollover, expiry, pooled or per-user allocation, tiered exchange rates per model). Multi-dimensional rate cards map different token types across different models without collapsing them into abstract units. Hybrid billing runs subscriptions, credits, token metering, and enterprise custom contracts in one system with one ledger. Revenue-per-customer sits next to cost-per-customer in real time.

PSP-agnostic: works with Stripe, Adyen, Checkout.com. Your payments stack can evolve independently of your billing architecture.

Pricing: free up to $3M billed, then 0.40% of volume.

Best for: AI-native companies where billing complexity is the core infrastructure problem. Particularly strong for companies running credits + subscriptions + enterprise contracts simultaneously, or companies that need PSP flexibility.

What to know: newer platform. Not designed for simple subscription-only businesses. The depth is the point, so if you're pre-PMF with a flat $49/month plan, this is more infrastructure than you need today.

Orb

A usage-based billing engine with strong engineering tooling. Ingests 250K+ events/sec. Billable metrics defined via SQL. Pricing compiler handles complex multi-dimensional logic. Credit system uses block-based architecture with individual expiry dates.

Why it ranks here: Orb gives engineering teams maximum control over how usage maps to charges. The pricing simulation feature lets you model changes against historical data before going live. For teams that want to own the pricing logic precisely, Orb is the most flexible tool available.

Pricing: custom (contact sales). Starts around $599/month.

Best for: engineering-heavy AI startups that want deep control over pricing logic and are already committed to Stripe.

What to know: Stripe-only for payments. That's a hard constraint if you need multi-PSP support, operate in regions where Stripe coverage is limited, or want optionality as your payments stack evolves. Requires significant engineering integration time.

Tier 2: Strong for specific use cases

Amberflo

Decoupled metering cloud and billing cloud that scale independently. Purpose-built for LLM and AI workloads with multi-model cost attribution, unified pricing tables across 100+ AI models, and an AI gateway with load balancing.

Why it's here: fastest time-to-value for AI-specific metering. Native credit system with real-time deduction. If you're routing requests across multiple LLM providers, Amberflo meters and bills across all of them.

Pricing: $8/10K LLM requests/month. Free trial (1M requests/30 days).

Best for: AI startups that need LLM-specific billing fast. Less suited for complex hybrid models combining subscription + usage + enterprise.

What to know: Stripe-focused for payments. Smaller customer base means fewer proof points at enterprise scale.

Lago

Open-source billing engine. Self-hostable or cloud-hosted. Ships pre-built pricing templates for OpenAI and Mistral models. Mistral AI uses Lago, generating 32,000+ invoices monthly with per-token billing.

Why it's here: only open-source option with native multi-PSP support (Stripe, Adyen, GoCardless, Cashfree). Wallet system supports up to 5 wallets per customer with metric-specific scoping. Flat-fee pricing means costs don't scale with your billing volume.

Pricing: open-source (free). Cloud from ~$99/month.

Best for: technical teams that want full control, need multi-PSP support, or are at a scale where percentage-based billing platform fees get expensive.

What to know: self-hosted requires Postgres, Redis, ClickHouse. No built-in dunning. Steep learning curve for non-technical teams. You're trading platform cost for engineering cost.

Metronome (now part of Stripe)

Before its acquisition, Metronome powered metering for OpenAI, Anthropic, Databricks, and NVIDIA. Processes billions of usage events daily on streaming infrastructure built on Apache Kafka. Separates metering, pricing, and contract management into distinct layers.

Why it's here and not Tier 1: Stripe acquired Metronome in January 2026. The product is strong, but the roadmap is now Stripe's roadmap. If you choose Metronome, you're choosing Stripe's ecosystem for billing and payments permanently. For companies that need PSP flexibility or want vendor independence, that's a structural constraint that didn't exist a year ago.

Pricing: custom (contact sales).

Best for: enterprise AI companies already deep in the Stripe ecosystem with dedicated billing engineering teams.

What to know: heavy implementation (weeks of configuration, SQL knowledge, data pipeline setup). No historical data backfilling. No native invoicing. The acquisition means evaluating Metronome now requires evaluating Stripe's long-term billing strategy.

Tier 3: Best for subscription-first companies adding AI

Chargebee

The most mature subscription billing platform in this comparison. 200+ integrations, deep accounting software connectivity (Salesforce, NetSuite, QuickBooks), enterprise-grade dunning and revenue recognition.

Why it's here: if your business is subscription-first and you're adding AI features that generate token usage on the side, Chargebee is the path of least disruption. You don't rip out your billing system for a feature.

Pricing: from $599/month.

Best for: mid-market SaaS with mature subscription billing adding AI features at the margin.

What to know: token metering isn't real-time. Credit ledger depth is limited. Adding serious AI billing on top of Chargebee typically requires the same custom engineering you were trying to avoid.

Stripe Billing (with LLM Token Billing)

Stripe launched LLM token billing in private preview. Auto-syncs token prices for OpenAI, Anthropic, and Google models. Markup-based pricing through the Stripe AI Gateway.

Why it's here: still fastest path to basic token billing if you're already on Stripe. The new feature directly solves the multi-meter problem that forced companies to collapse token types into abstract billing units.

Pricing: 0.7% of billing volume + Stripe processing fees (total often ~1.5%).

Best for: early-stage AI startups already on Stripe with simple pricing.

What to know: still private preview. Percentage-based pricing compounds at scale. Credit systems are limited. And you're locked to Stripe. If you're going to build on Stripe's billing anyway, evaluate whether Metronome (now part of Stripe) or the native token billing feature is the better path.

Comparison table at a glance

How to choose

Three questions determine your choice:

1. Are credits a core part of your pricing? If you sell credit packs with rollover, expiry, team pooling, and model-specific exchange rates, you need a platform where credits are a financial primitive. Solvimon and Orb handle this natively. Chargebee and Stripe don't. Lago sits in between with flexible wallets but more engineering required.

2. Do you need billing and payments from different vendors? If yes, your options are Solvimon (Stripe, Adyen, Checkout.com), Lago (Stripe, Adyen, GoCardless, Cashfree), or Chargebee. Every other platform on this list locks you to Stripe.

3. How fast does your pricing change? AI companies change pricing more frequently than any other software category. New models, new token types, competitive pressure, enterprise negotiations. If a pricing change requires an engineering sprint, you're losing weeks of margin every time the market moves. Evaluate how each platform handles rate card updates and whether your team can make changes without code.

The AI billing market consolidated around Stripe in early 2026. That's worth understanding before you build your stack. If Stripe is the right long-term payments partner for your business, the ecosystem is strong. If you want optionality, the platforms that offer it are Solvimon, Lago, and Chargebee, each at different levels of AI billing depth.

For platform deep dives, see: Token billing for AI: 7 platforms compared →

For pricing model guidance, see: AI credit pricing models: how tokens, credits, and hybrid billing actually work →

Solvimon has credits, tokens, hybrid billing, PSP-agnostic. Free up to $3M billed.