Tether to End USDT Redemptions on Bitcoin Cash, Algorand and Beyond
Stablecoin issuer Tether is ending its USDT support for five blockchains effective on September 1, the company announced on Friday, ending redemptions and freezing the remaining assets on those blockchains.
Last June, the firm ended its minting function on Algorand and EOS (now called Vaulta), meaning it would no longer issue new stablecoins on those chains. In 2023, it announced the same for Bitcoin Cash, Kusama, and Omni Layer Protocol.
Now, Tether has put a hard end date on its stablecoin support on the group of five “legacy” blockchains as part of its efforts to “optimize infrastructure, align with community usage trends, and refocus resources toward high-utility, actively developed blockchains.”
The firm acknowledged that while the networks supported Tether’s early growth, the share of trading volume for its stablecoin has declined dramatically in the last few years.
“As the digital asset ecosystem evolves, Tether remains committed to adapting alongside it,” said Tether CEO Paolo Ardoino in a statement. “Sunsetting support for these legacy chains allows us to focus on platforms that offer greater scalability, developer activity, and community engagement—all key components for driving the next wave of stablecoin adoption.”
Holders of USDT on the aforementioned blockchains are encouraged to redeem their tokens as soon as they can, or request an issuance of USDT on a supported blockchain.
Moving forward, it plans to focus its support for layer-2 networks and growing blockchain ecosystems.
Stablecoins have been a key theme in the crypto industry of late, highlighted by the U.S. push for regulatory clarity for the tokens with the GENIUS Act. U.S. Treasury Secretary Scott Bessent recently suggested that the tokens–which are typically anchored to the price of the U.S. dollar–could help bolster U.S. dollar supremacy.
Tether’s USDT stablecoin is the largest stablecoin in crypto with nearly $160 billion in minted stablecoins in circulation according to CoinGecko’s market capitalization data.
Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.
You may also like
Fear is the biggest short! Morgan Stanley calls for bottom-fishing in semiconductors: land and electricity shortages are not a problem, approved projects can't meet demand
Morgan Stanley believes that the recent sell-off in the semiconductor sector has been excessive, and that market panic rather than fundamentals is the biggest risk. Driven by demand for AI infrastructure, downstream orders continue to accelerate, with semiconductor supply remaining the core bottleneck. LPS constraints actually make growth more stable. The sector may fluctuate within a range in the short term and is currently near the bottom; prospects for the computing power and storage subsectors are favorable.

Indian Rupee extends rally amid continued FIIs buying, lower oil prices

Hashrate orders are booming, why is "AI trading" falling out of favor? JPMorgan reveals the time lag between AI investment and productivity realization
Joseph Lupton from the JP Morgan Global Economic Research Team pointed out in a research report on November 10 that recent improvements in labor productivity have been driven more by capital deepening and increased intensity of factor utilization. The broad efficiency gains from AI, resulting from process reconstruction, data integration, and organizational adjustments, will still take time to materialize. This means orders for chips, servers, and electrical equipment may grow first, but continuous investment returns for computing power operators and end users may not arrive at the same pace.
AI investment enters the "Trough of Disillusionment", the next 18 months will be a life-or-death test!
Goldman Sachs believes that the AI investment cycle is currently in the "trough of disillusionment," but this is not the first time. The core contradiction lies in the fact that the business models of new cloud computing providers are highly dependent on end-user returns from AI spending, while currently "there are basically zero companies that can attribute profits to AI." Social Capital founder Palihapitiya has clearly defined an 18-month key window, during which the market will decide which AI business models are sustainable and which are not.

