Artemis Crypto Payment Card Report: $18 Billion Market Size, The Silent Explosion of Crypto Payments

marsbitPublicado a 2026-01-21Actualizado a 2026-01-21

Resumen

Artemis Research reveals that the crypto payments card market has grown into a $18 billion industry, with monthly transaction volumes increasing 15-fold since early 2023. The report breaks down the crypto card stack into three layers: Networks (Visa and Mastercard), Issuers & Program Managers (e.g., Baanx, Bridge), and Consumer Apps (wallets and exchanges like MetaMask and Phantom). Visa dominates with over 90% of on-chain card transaction volume, largely due to early infrastructure partnerships. A key structural shift is the rise of full-stack issuers like Rain and Reap, which now issue cards and settle directly as Visa Principal Members—bypassing sponsor banks for greater control and better economics. Geographic usage varies: In India, crypto cards serve as collateralized credit solutions, while in Argentina, they function as inflation-hedged stablecoin debit cards. In developed markets, crypto cards target high-value users who hold significant stablecoin balances and seek to spend them. The report concludes that as stablecoin adoption grows, crypto cards will scale accordingly, acting as essential infrastructure for bringing digital dollars into the real economy.

Author: Artemis

Compiled by: Deep Tide TechFlow

Deep Tide Guide:

Crypto payments are undergoing a silent "great power shift." The latest research from Artemis shows that the crypto card market has surged from the fringes in early 2023 to a massive $18 billion annualized size, with monthly transaction volume increasing 15-fold in just two years.

This article deconstructs the three layers of the crypto payment stack and reveals a surprising figure: Visa accounts for over 90% of on-chain card transaction volume. More importantly, the industry is experiencing a structural shift towards "full-stack issuance." Companies like Rain and Reap are bypassing traditional banks by connecting directly to Visa, completely rewriting the economic model. From crypto-collateralized credit in India to daily stablecoin payments in Argentina, crypto cards are becoming key infrastructure for bringing digital dollars into the real world.

Full text as follows:

Big news: We just released the industry's most detailed research report on Crypto Cards.

Not because it's a niche market, but because it has quietly grown into an $18 billion market. In early 2023, monthly transaction volume for crypto cards was only around $100 million. Today, that number has exceeded $1.5 billion.

To do this, we spent weeks digging deep into the data, the infrastructure, and the companies actually building this stack. Here are our key findings:

First, let's look at what's actually happening. Crypto cards aren't about replacing Visa or Mastercard; they're about leveraging them.

Stablecoins fund the transactions, and Cards provide the merchant acceptance environment.

The stack is divided into 3 layers:

  • Network Layer: Visa, Mastercard
  • Issuers & Program Managers Layer: Baanx, Bridge, etc.
  • Consumer Apps Layer: Wallets, Exchanges (e.g., MetaMask, Phantom)

This is precisely where the power struggle is most intense.

Although both Visa and Mastercard each have over 130 crypto partnerships...

Visa accounts for over 90% of on-chain card transaction volume. The reason lies in its early and deep partnerships with the Infrastructure Layer.

The biggest structural shift: Full-stack issuers.

Companies like Rain and Reap can now issue cards and settle directly as Visa Principal Members.

No sponsor bank needed. More control. Better economics.

Geographic distribution reveals the real use cases. India: With $338 billion in cryptocurrency inflows. The opportunity here is crypto-collateralized credit (because UPI has already won in debit payments). Argentina: The practical application is stablecoin debit cards as an inflation hedge.

In developed markets, crypto cards don't solve a "critical need."

They target a new, high-value user base: those who already hold significant stablecoin balances and want to spend them.

Our view is simple: Stablecoins will continue to grow, and crypto cards will scale accordingly.

They are the infrastructure for bringing digital dollars into the real world.

This post is just the key highlights. Read the full report for the complete deep dive.

Lecturas Relacionadas

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

AI is reshaping the labor market's value proposition. The traditional four-year college degree is losing its appeal as a guaranteed career path, while skilled blue-collar trades like electricians, welders, and plumbers are experiencing historic demand and wage premiums. This shift is driven by dual pressures: AI's displacement of certain white-collar roles and a booming need for physical infrastructure and data center construction. Data confirms the trend. In the U.S., vocational school revenue surged, and a significant portion of recent layoffs are AI-related. Surveys show a majority of Gen Z adults plan to pursue blue-collar work, citing better job security against AI automation. Vocational education interest has exploded recently. Experts cite a psychological shift as younger generations seek tangible, AI-resistant careers and avoid high student debt. In many cases, salaries for skilled trades now match or exceed those requiring a bachelor's degree. In South Korea, semiconductor vocational high schools boast near-total employment, with graduates securing high-paying roles at companies like Samsung. The shortage is structural, exacerbated by a retiring baby boomer workforce and massive infrastructure projects. Companies like JPMorgan Chase, Meta, and Lowe's are investing heavily in training programs. However, overcoming historical stigma and a "perception gap" around trade careers remains a key challenge to closing the talent gap.

marsbitHace 51 min(s)

From South Korea to the United States: Blue-Collar Jobs Are Becoming Increasingly Popular, Thanks to AI

marsbitHace 51 min(s)

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

Qualcomm reported its Q3 FY2026 results (ending June 2026), with revenue of $9.95B, down 4% YoY but above expectations. Gross margin declined to 53.1%, pressured by rising costs across manufacturing and memory. Key business segments showed mixed performance: Handset revenue fell 19.6% YoY to $5.09B, dragged by an 11% decline in non-Apple Android shipments and weaker high-end mix. Conversely, Automotive revenue surged 61% to $1.59B, and IoT grew 9% to $1.83B. Core operating profit dropped 41% YoY due to margin compression and higher expenses. Management's Q4 FY2026 guidance projects revenue of $9.7B-$10.5B, in line with consensus, but Non-GAAP EPS guidance of $2.05-$2.25 fell short of expectations. Amidst persistent weakness in its core handset market, Qualcomm is pursuing growth in AI, focusing on Edge AI (smartphones, PCs, automotive) and Data Center AI. Its data center strategy includes four pillars: AI accelerators (e.g., AI200), commercial CPUs (Dragonfly C1000), custom silicon, and connectivity solutions. While these initiatives initially boosted its stock, concerns over AI capital expenditure sustainability have since erased those gains. The company targets $5B in data center revenue for FY2027 and $15B for FY2029. The report concludes that with the traditional handset business still under pressure, the data center opportunity is currently viewed as a longer-term option, and a more conservative valuation based on core operations may be warranted until AI contributions materialize.

marsbitHace 55 min(s)

Qualcomm: AI Hype Subsides, When Will Smartphones Emerge from the Gloom?

marsbitHace 55 min(s)

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

At the 2026 YC Startup School, Jeff Dean outlined his vision for AI's next phase, shifting focus from simply scaling models to building intelligent, autonomous systems. He believes AI's progress is no longer just about creating smarter models, but about integrating them into systems capable of long-term, iterative work, automated experimentation, and continuous learning. This evolution moves the competition from "who has the bigger model" to "who can best organize intelligence." Dean suggests AI capabilities are now comparable to a junior engineer, enabling the automation of complex workflows. However, the true challenge and opportunity lie in managing these AI "workers" at scale. He emphasizes the importance of **context engineering**—structuring tools, memory, and feedback loops—over raw model power. For startups, this means building deep expertise in niche domains where general models currently fail (near 0-1% success rates), leveraging proprietary data, specialized tools, and domain-specific evaluators. A recurring theme is re-examining fundamental constraints. Dean's past work, like moving Google's search index to memory or creating the TPU, stemmed from questioning outdated assumptions about hardware and cost. He sees similar inflection points today, particularly in **specialized inference hardware** to drastically reduce latency and energy consumption for real-time Agent operation. Notably, he points out that in modern AI systems, the dominant cost is often not computation but **data movement**. Reliable, long-running Agents require robust system design, borrowing concepts from distributed computing like checkpointing, state management, and parallel exploration to handle failures and maintain progress over days or weeks. As AI automates execution, the scarcest human skills will shift to **defining clear specifications**, **judging what problems are worth solving** (taste), and designing effective feedback loops. Ultimately, Dean's framework prioritizes understanding the problem deeply, identifying the true bottlenecks, and systematically building closed-loop systems where AI can not only perform tasks but also improve AI itself.

marsbitHace 56 min(s)

From TPU to Self-Evolving Agents: How Jeff Dean Predicts the Next Step in AI

marsbitHace 56 min(s)

Trading

Spot
活动图片