Agent-to-agent payments on Coinbase’s Base expanded from roughly 1,500 cumulative x402 transactions in mid-2025 to more than 138 million by Q3 2026, according to Chainalysis. More than 87% of payments during the 16 months ending September 2026 were between one-hundredth of a cent and 10 cents, showing that the early use case is inexpensive, automated access to digital services rather than ordinary retail checkout.
The reported growth, in context
Chainalysis describes cumulative x402 activity on Base rising from about 1,500 transactions in mid-2025 to over 138 million by the end of the period it analyzes. In the report’s quarter-based framing, that endpoint is Q3 2026, the quarter ending September 2026. The figures count transactions, not unique agents, people, merchants or dollars settled.
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| Measure | Reported result | Qualification |
|---|---|---|
| Starting activity | Approximately 1,500 cumulative transactions | Observed around mid-2025 |
| Ending activity | More than 138 million cumulative transactions | Q3 2026 period, ending September 2026 |
| Payment concentration | More than 87% between $0.0001 and $0.10 | 16 months ending September 2026 |
| Most common band | One to 10 cents | Within the same Chainalysis analysis |
That scale-up is striking, but a transaction count alone cannot show whether the activity is profitable, economically independent, or representative of broad consumer adoption. Automated retries, testing, repeated calls by a small number of applications and other high-frequency behavior can all increase transaction totals.
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Payment inside a software request
x402 is a payment protocol developed by Coinbase that lets software agents pay for web resources directly as part of a request. Instead of a person entering card details for every small purchase, an agent can request a metered resource—such as data, an API response or model inference—and settle the associated charge programmatically.
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The design targets machine-to-machine commerce. A service can require payment before returning a response, while the calling software supplies the payment as part of the request flow. This is different from using a cryptocurrency wallet as a manual checkout method: the intended payer is autonomous software operating within rules set by its developer or owner.
Why Base appears in the report
Base is the principal network for the x402 activity measured by Chainalysis. The report therefore describes a specific deployment and its observed usage, not every blockchain-based agent-payment system. The figures should not be read as a census of all AI-agent payments.
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Why the payments are mostly below 10 cents
Traditional card networks are optimized for consumer purchases, not thousands of sub-dollar requests. Fixed processing costs, authorization overhead and risk controls can make a one-cent or sub-cent charge uneconomic. Stablecoin settlement can cost less than a cent, allowing a service to charge for each small API call, data lookup or inference event instead of forcing customers into subscriptions or large prepaid bundles.
That is why the distribution is concentrated at the very low end: over 87% of payments in the cited period fell between one-hundredth of a cent and 10 cents, with one-to-10-cent payments the most common range. These are prices suitable for metered access, where an agent pays only for the resource it consumes.
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Circle summarized the emerging division of labor this way, as quoted by Chainalysis: “card rails for consumer-prompted agent payments, stablecoin rails for machine-to-machine settlements that are too small for card economics.” In practice, a person might authorize an agent’s larger purchase by card, while the agent uses stablecoins for repeated low-value calls between software services.
Evidence that agents are returning
Chainalysis reports a change in wallet persistence among wallets receiving a second funding within 30 days. For wallets first funded in Q3 2025, 70.6% received another funding within that window. For wallets first funded in Q2 2026, the comparable share was 89.3%, after those wallets’ 30-day measurement windows had closed.
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| Wallet cohort | Wallets with a second funding within 30 days |
|---|---|
| First funded in Q3 2025 | 70.6% |
| First funded in Q2 2026 | 89.3% |
Repeat funding is a sign that some applications or users continued operating after an initial test. It does not identify the funding source, reveal revenue per wallet or establish that the activity is profitable. Chainalysis still characterizes agentic commerce as being in an experimentation phase, even while noting signs of maturation.
What the 138 million figure proves—and what it does not
- It does show substantial measured usage: the reported Base transaction total moved from a few thousand to more than 138 million over roughly the period covered.
- It shows a strong micropayment fit: most observed payments were priced below 10 cents, where conventional card economics are often unsuitable.
- It does not measure unique adoption: one agent can generate many transactions, and the report’s headline number is cumulative.
- It does not prove consumer scale: the evidence concerns machine-payment activity and repeat wallet funding, not the number of ordinary people using AI agents.
- It does not establish business success: transaction volume does not reveal margins, service quality, fraud losses or whether merchants retain customers.
How this approach compares with other payment rails
The available evidence supports a functional comparison, not a complete performance benchmark against every competing network or protocol.
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| Dimension | x402 on Base | Card-based payment | What remains unestablished |
|---|---|---|---|
| Settlement economics | Stablecoin settlement can cost less than a cent, supporting tiny charges. | Sub-dollar and sub-cent charges can be poorly suited to card-fee economics. | No apples-to-apples fee or latency benchmark is provided. |
| Autonomous software | Payment is designed to occur directly within a web request. | Cards are generally designed around a consumer-initiated purchase and authorization. | The report does not quantify implementation effort or failure rates. |
| Use-case fit | Metered data, APIs, model inference and other digital resources. | Consumer-prompted purchases, including larger transactions. | Which rail wins for a particular product depends on its controls and customers. |
| Repeat usage | Wallet second-funding rates rose from 70.6% to 89.3% across the cited cohorts. | No comparable figure is supplied here. | Repeat funding is not the same as profitable retention. |
| Reach and reliability | Evidence in this report is specific to the Base deployment. | Geographic and regulatory availability varies by issuer and country. | The cited material does not provide a complete geographic, regulatory or endpoint-reliability comparison. |
What to watch as the experiment develops
The next meaningful tests are not simply whether transaction totals keep rising. Developers and users will need dependable merchant endpoints, spending limits for autonomous wallets, clear recovery procedures when a request fails, and evidence that the value of the returned data or computation exceeds the payment and operating costs. Adoption will look more mature when activity reflects durable applications and repeat economic demand rather than short-lived experiments.
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