I just dove into the latest Dune data on stablecoins, and there’s a lot of interesting activity that most people are ignoring. Everyone keeps citing that $300 billion in circulation number, but that’s just the surface.

The stablecoin market has really exploded. In January, the total supply hit $304 billion, a 49% increase compared to last year. Ethereum continues to dominate with $176 billion (58% of the total), Tron with $84 billion (28%), Solana with $15 billion, and BNB Chain with $13 billion. USDT and USDC still control 89% of the market, but what caught my attention is the movement of challengers.

USDS grew 376% to $11.5 billion. PYUSD surged 753% to $3.4 billion. RLUSD jumped from $58 million to $1.1 billion. USD1 went from zero to $2.1 billion. This is a real diversification movement; it’s no longer just USDT and USDC dominating everything.

But here’s the critical point: knowing who holds these assets completely changes the analysis. Centralized exchanges hold $80 billion in stablecoins, up from $58 billion a year ago. Large holders have $39 billion. Yield protocols nearly doubled to $9.3 billion. Significantly, 23% of the supply is in addresses that are completely unknown — for on-chain data, that’s an extremely high identification rate.

The transfer volume in January was staggering: $10.3 trillion. Base led with $5.9 trillion despite having only $4.4 billion in supply. Ethereum with $2.4 trillion, Tron with $682 billion, Solana with $544 billion. But the most interesting part is that USDC transferred $8.3 trillion — almost five times more than USDT — even though its supply is 2.7 times smaller. USDC circulates much faster, by far.

When you look at circulation velocity, the story changes completely depending on the chain. USDC on Base has a turnover rate of up to 14 times per day. On Solana and Polygon, it’s around once. USDT on BNB Chain reaches 1.4 times, but on Ethereum, it’s just 0.2 times — over $100 billion practically sleeping there. USDe and USDS have slower speeds because they were designed as yield-generating stablecoins.

What really impressed me was the granularity of activity data. Of the total transfers, $5.9 trillion went to DEX infrastructure for liquidity provision and withdrawal. $376 billion in direct swaps. Flash loans moved $1.3 trillion. Issuer operations — minting, burning, rebalancing — totaled $1.06 trillion, nearly five times the record of $420 billion from a year ago. This shows that stablecoins are truly being used as fundamental infrastructure, not just for speculation.

Now, on concentration: USDT, USDC, and DAI have quite broad distribution, with the top 10 holders controlling only 23-26% of the supply. But other stablecoins tell a completely different story. USDS has 90% concentrated in 10 wallets. USDF has 99% in 10 wallets. USD0 is extreme, with 99% and an HHI of 0.84 — almost monopolized by one or two addresses.

What I found particularly relevant is that the dataset now tracks over 200 stablecoins representing 20+ fiat currencies. Euro with 17 tokens and $990 million in supply. Brazilian real with $141 million. Japanese yen with $13 million. And tokens in NGN (Nigerian naira), KES (Kenyan shilling), ZAR (South African rand), TRY (Turkish lira), IDR (Indonesian rupiah), and SGD. The infrastructure for stablecoins in local currencies is being built. Just think: $420 in naira represents a very different amount, and having stablecoins in local currencies completely changes liquidity access for emerging markets.

The total volume of non-dollar stablecoins is only $1.2 billion so far, but there are 59 tokens available across six continents. This is just the beginning.

What makes this dataset unique is that each transfer is classified into nine different activity categories. Each balance is segmented by holder type. This turns noisy blockchain logs into structured, comparable data. The depth here allows us to answer questions we didn’t even know how to ask yet: what’s the flow of funds between chains for euro stablecoins? How does concentration change in the days before a depegging event? What’s the correlation between issuer minting/burning and market pressure?

This is exactly the kind of dataset that supports real institutional analysis, research reports, risk modeling frameworks, and compliance monitoring. It’s not just a pretty number — it’s the infrastructure that financial institutions and regulators need to truly understand this $300 billion market.