Morph Integrates USDT0, Unlocking Access to the World’s Largest Stablecoin Liquidity Pool

TheNewsCryptoPublished on 2026-02-13Last updated on 2026-02-13

Abstract

Morph, an Ethereum-based payments settlement network, has integrated USDT0, the omnichain Tether liquidity network powered by LayerZero. This integration provides Morph with direct access to unified USDT liquidity across more than 18 blockchains, eliminating the need for traditional bridges and wrapped tokens. USDT0 uses a burn-and-mint mechanism, creating a single consistent asset across all supported networks and reducing liquidity fragmentation and counterparty risk. Designed specifically for payments, Morph offers sub-300ms block times and zero-fee stablecoin transfers, targeting merchant settlement, remittances, crypto card issuance, and treasury management. With USDT's market cap exceeding $185 billion, developers on Morph can now tap into the world’s largest stablecoin liquidity pool from day one. This enables seamless cross-border transactions, deeper DeFi liquidity, efficient merchant payment processing, and predictable cross-chain operations for financial institutions. The collaboration between USDT0 and Morph aims to advance unified omnichain liquidity, making stablecoins truly borderless and supporting next-generation financial applications.

Singapore, Singapore, February 13th, 2026, Chainwire

Ethereum-based payments settlement network Morph has integrated USDT0, the omnichain Tether liquidity network powered by LayerZero. The move gives Morph, which aims to become the settlement layer for everyday money, direct access to unified USDT liquidity across 18+ blockchains.

For developers building payment apps, merchant tools or even DeFi protocols on Morph, this means they can tap into a massive, ready-made liquidity pool from day one without the headache of managing a dozen different bridged token contracts.

No more bridges. No more wrapped tokens

Traditionally, using USDT on another blockchain requires a bridge. This process locks the original tokens and mints a new, “wrapped” version on the destination chain.

These wrapped variants are not the same asset. They are separate tokens backed by assets held in complex smart contracts, leading to liquidity fragmentation — where the same currency is trapped in isolated pools — and introducing counterparty risk if a bridge fails.

USDT0 proposes a different model. Instead of locking and minting, it uses a burn-and-mint mechanism. To move USDT from Chain A to Chain B, tokens are burned on Chain A and minted directly from Tether’s canonical supply on Chain B.

As a result, USDT0’s Omnichain Fungible Token (OFT) standard creates a single, consistent asset across all supported networks.

What USDT0 enables for builders on Morph

While many L2s compete for general DeFi activity, Morph is engineered for a specific vertical: payments. Its architecture — featuring sub-300ms block times and zero-fee stablecoin transfers — targets merchant settlement, remittances, crypto cards issuance, and treasury management.

For such use cases, deep and frictionless liquidity is non-negotiable. USDT, with a market cap exceeding $185 billion, represents the largest pool of stablecoin liquidity in crypto.

As the USDT0 integration is now live on Morph mainnet, developers on Morph can integrate what is effectively a universal USDT, slashing technical overhead and simplifying cross-chain user experience, which means:

Payment applications can process cross-border transactions with instant settlement and minimal overhead.
DeFi protocols can access deeper liquidity without managing multiple stablecoin variants.
Merchant platforms can accept stablecoin payments with seamless conversion and settlement.
Financial institutions can execute treasury operations with predictable behavior across chains.

The combination of USDT0’s unified liquidity and Morph’s payment-optimized infrastructure lays a powerful foundation for next-generation financial applications.

We’re excited to work alongside the USDT0 team in advancing the vision of unified, omnichain liquidity that makes stablecoins truly borderless.

Money at the speed of life.

About Morph

Morph is an Ethereum-based, payments-first settlement layer and the native onchain home of BGB, focused on building the foundation for global consumer finance onchain. Morph supports real-world financial activity across payments, savings, identity, and rewards, enabling scalable, onchain settlement for consumer and business use. Guided by the Morph Foundation, the network connects more than 120 million users through the Bitget and Bitget Wallet ecosystems.

Contact

Andrew Azarias
Andrew.azarias@morphl2.io

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit1h ago

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit1h ago

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit1h ago

marsbit1h ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbit1h ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbit1h ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbit1h ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbit1h ago

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

In today's TechFlow Intelligence Briefing, several major tech stories highlight a growing theme of trust and credibility gaps across AI, crypto, and finance. AI company Anthropic has publicly called for a global pause in AI development, citing risks from Claude's "recursive self-improvement." Ironically, this coincides with reports the company is preparing for a massive IPO targeting a near $1 trillion valuation. This perceived hypocrisy, coupled with widespread user complaints about Claude's declining performance, is sparking debate over whether the safety warning is genuine or a competitive tactic. Meanwhile, in a substantive security move, Anthropic open-sourced a framework for AI-powered vulnerability discovery. In the crypto market, Bitcoin's price drop below $61,000 triggered over $1.16 billion in liquidations, flipping the market into a state where more BTC is held at a loss than at a profit, a historical bearish signal. On the corporate front, SpaceX's highly anticipated IPO is generating immense Wall Street excitement, with Goldman Sachs projecting 100x revenue growth by 2030. However, the S&P 500 has refused to fast-track the company's inclusion post-IPO, potentially limiting immediate institutional demand. Separately, ByteDance's AI app Doubao lost over 6 million monthly active users after introducing a subscription model, highlighting the challenges of AI monetization. Other notable developments include Nvidia certifying HBM4 memory from Samsung, SK Hynix, and Micron; Cloudflare's acquisition of front-end tooling company VoidZero; and its CEO warning that bot traffic now exceeds human traffic online. The underlying narrative connects these events: a trust crisis. From AI firms' contradictory actions and crypto volatility to the clash between SpaceX's hyped narrative and institutional rules, a pattern is emerging where stated intentions and actual practices are increasingly misaligned.

marsbit1h ago

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

marsbit1h ago

Trading

Spot

Futures

Morph Integrates USDT0, Unlocking Access to the World’s Largest Stablecoin Liquidity Pool

Abstract

Contact

Related Questions

Related Reads

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Token Inefficient, Economy Tokenless

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

Trading