Credit-based pricing explained: A complete guide for SaaS and AI companies

In the past year, credit-based pricing has become increasingly popular, with industry giants like Microsoft, Salesforce and Cursor all switching to partial credit based pricing models for specific product offerings.

This is part of the shift toward usage-based pricing (UBP) models.

Customers want to pay for usage, while finance teams want predictable revenue that doesn’t swing wildly each month.

Now, while usage-based billing aligns costs with value, it makes forecasting harder and invoices tougher to explain. Credit-based pricing has emerged as a compelling middle ground, combining the flexibility of pay-as-you-go with the predictability of prepaid commitments. That’s why it’s gaining traction across AI, API-first, and fintech companies, where usage can vary dramatically.

In this guide, we’ll unpack what credit-based pricing is, how it works, why it’s important, and how to implement it effectively.

What is credit-based pricing (and how it works)

Credit-based pricing is a model in which customers pay for usage upfront in the form of credits. A credit is an internal currency that represents measurable units of value based on what type of products or services the company is selling.

For example, it could represent an API call, a gigabyte of data, 1000 tokens, or 10 transcription minutes. As customers use the product, credits automatically deduct from their balance in real time.

Think of it like a prepaid phone plan. A customer might buy 10,000 credits for $1,000, with each API call costing 10 credits. They can use those credits at their own pace (e.g., 5,000 this month and 15,000 next) and top up anytime. This gives customers flexibility and control while ensuring businesses get money upfront.

Most AI and SaaS companies structure credit packages into tiers (e.g., 1,000, 10,000, or 100,000 credits), often with volume discounts that reward larger commitments. Customers can monitor their balance through a dashboard, receive low-credit alerts, and easily top up online. 

While most companies allow credit roll-overs from month to month, some will have annual expiration periods to encourage renewals and maintain predictable revenue cycles.

If you’re evaluating how credits fit within your overall pricing strategy, it’s worth reading our deep dive on AI pricing models. It breaks down how credit-based, usage-based, and hybrid pricing structures coexist in today’s AI and SaaS ecosystems.

How is credit-based pricing different from other models?

The credit-based pricing model builds on usage-based billing, but adds a key differentiator: pre-payment.

Instead of being billed after the fact like in pay-as-you-go (PAYG) models, customers purchase credits upfront and draw from them as they use the product.

This maintains the flexibility of usage-based billing while introducing greater predictability and budget control.

For example, an AI image-generation platform might charge a monthly subscription for basic access, while letting users purchase credits to generate additional images, upscale resolutions, or use premium models. The credits act as a flexible usage layer on top of a recurring base plan.

This hybrid approach ensures predictable recurring revenue for the business while giving customers control over their spend and the freedom to scale usage as needed.

Why the credit-based pricing model is gaining popularity

For customers, credits feel transparent and fair. They pay for what they use, when they use it, without surprise overages or wasted licenses. For finance teams, prepaid credits lock in committed spend, making revenue more predictable even when usage fluctuates. 

Credits also drive engagement. Once customers prepay, they’re more likely to explore, experiment, and expand, effectively turning credits into a built-in retention mechanism. And for AI and API-first businesses with spiky workloads and high compute costs, the model offers budget control for buyers and upfront cash flow for vendors.

In short, credit-based pricing fits both AI-native companies and the modern SaaS landscape: usage-driven, customer-centric, and designed for both scale and stability.

Proven credit-based pricing models: Examples from OpenAI, HubSpot, Clay, and more

From CRM tools to AI APIs, leading companies are adopting credits to let users pre-purchase access, control spend, and scale usage on demand.

Below is a comparison of how OpenAI, HubSpot, Salesforce, Microsoft, and Clay use credit-based monetization in different ways.

The best tracking tools for credit and consumption-based pricing

As more AI and SaaS products shift from flat subscriptions to pay-as-you-go models, companies need monetization platforms and billing tools that automatically meter usage and manage credits. 

The right tools automate these tasks so product, finance and engineering teams can focus on growth instead of building custom billing systems.

AI monetization platforms for credit based pricing

• Alguna: A modern AI monetization platform for your entire quote-to-cash workflow built for AI and SaaS companies. Alguna combines CPQ, usage metering, billing, invoicing and even e-signatures in one system. It captures every usage event in real time (API calls, tokens, etc.) and supports all usage-based and hybrid models. Alguna natively handles credit/bundle plans: customers can prepay for credits or tokens that draw down with use. This makes it ideal for companies who need flexible pricing, for example, mixing flat subscriptions with token-based overages–without coding a billing solution.
• Metronome: A unified monetization infrastructure designed for the AI era. Metronome provides real-time usage metering, flexible pricing rules, and revenue analytics in one system. Finance teams use it to monitor credit usage and customer spend live. Metronome is ideal for companies that need to tie raw usage data (API calls, query counts, etc.) into custom billing logic. It offers dashboards and alerts for teams, ensuring usage-based charges and credit balances are accurate without manual coding.
• Orb: A developer-friendly billing engine that ingests raw product usage events and lets teams define pricing logic on top. For example, you could build token-based charges, per-run fees, or multi-attribute rates. Orb is built to handle high volume in real time, replacing legacy batch billing.
• Zuora: An enterprise subscription billing suite that handles very complex usage and credit scenarios. Zuora supports a wide range of usage charge models (flat fees, per-unit, tiered, volume, overage, high-water mark, etc.). Critically, Zuora offers prepaid credit schemes: customers can prepay for a quantity of usage or spend, and Zuora will draw that down (“Prepaid with Drawdown”, “Minimum Commitment” features).
• Lago: An open-source (self-hosted) usage billing platform designed for “modern monetization streams.” Lago supports pay-as-you-go and hybrid plans out of the box. Notably, it has built-in prepaid credit bundles and drawdown rules for usage. In other words, you can sell customers a block of credits or tokens and Lago will automatically decrement their balance. It’s a solid choice for engineering-led teams.

5 examples of when credit-based pricing might not be the right fit

Credit-based pricing isn’t a one-size-fits-all model. While it offers flexibility and predictability, there are situations where it can add friction rather than clarity.

1. When simplicity beats flexibility
If your product has a single clear usage metric, such as “per user” or “per GB stored,” adding credits may overcomplicate things. Credits work best when unifying multiple features or variable usage patterns, rather than when a single metric drives cost and value. 

For example, an API platform might use credits that cover both data storage and API calls, letting customers draw from a single shared balance rather than tracking separate usage limits for each feature.

2. When customers need raw transparency
Some buyers, especially in technical or enterprise markets, prefer to see costs broken down in concrete terms, like CPU hours or API calls. For them, credits can feel abstract or opaque unless you clearly map each credit to usage.

3. When usage is stable
If customers use roughly the same amount every month, credits don’t add much benefit. In these cases, straightforward subscriptions or tiered plans usually make more sense as predictable usage doesn’t require flexible pricing.

4. When your systems aren’t ready
Managing credits requires solid infrastructure for real-time metering, balance tracking, and reporting. If your billing tools or finance workflows can’t handle this complexity, it’s better to start simple and evolve later.

5. When it risks commoditizing your product
If positioned poorly, credits can make your product feel like a utility, where buyers focus only on the costs of credits rather than the overall value. To avoid that, pair credit models with strong value messaging or bundle them into broader tiers.

In a nutshell, credit-based pricing is most effective when it simplifies, not when it adds complexity. For many companies, the best approach is hybrid: use credits for variable, usage-heavy features and simpler pricing for the rest.

Frequently asked questions about credit-based pricing

How are credits priced?
Credits are typically priced based on a mix of cost, value, and expected usage. Companies decide what one credit equals (e.g., 1 API call = 1 credit) and sell them in tiers with volume discounts, meaning the more you buy, the cheaper each credit is. Enterprise customers often negotiate custom rates. 

Do unused credits expire?
It depends on the vendor. Many credits expire after 12 months or at the end of a contract to encourage renewals and manage accounting. Some roll over month-to-month or carry into renewals if the customer stays active. The key is transparency: vendors should clearly communicate expiration policies and send reminders before credits lapse.

What happens if a customer runs out of credits?
When a customer’s credit balance hits zero, one of two things usually happens:

1. Prevent and prompt: The system pauses usage immediately. The customer receives an alert (often at 50%, 10%, and 0% remaining) and must top up before continuing. This ensures full control over spend.
2. Allow and bill: The system allows usage to continue and automatically charges for overages or adds another credit bundle to the account. This prevents service interruption but can lead to additional charges.

Can credits be shared across users or teams?
Yes, many B2B systems use pooled credits at the org level, so multiple users draw from a shared balance.

Building flexibility into your pricing future

Credit-based pricing represents the next step in modern monetization, helping businesses link revenue to customer value while keeping cash flow predictable.

Success, however, comes down to execution. The companies winning with credits keep pricing simple, transparent, and adaptive. They also treat credits as a UX tool, not a gimmick, making billing intuitive and value clear.

As billing technology and AI-driven analytics evolve, maintaining that simplicity at scale will become even easier. Expect to see more hybrid models that offer flexibility without chaos. The more dynamic your model, the more room you have to grow with your users.

Ultimately, pricing isn’t static. Whether you’re scaling an AI product or a traditional SaaS, your model should evolve with your customers. Credit-based pricing makes that possible, aligning cost, value, and usage in real time. The companies that master this flexibility today will define how software monetization works tomorrow.