Trump Media, Crypto.com, and Yorkville Launches $6.42B CRO Treasury

TheCryptoTimesPublicado em 2025-08-03Última atualização em 2025-08-27

Nasdaq listed Yorkville Acquisition Corp. and Trump Media & Technology Group Corp. have announced a partnership with Crypto.com exchange for a $6.24 billion CRO treasury. The treasury, called Trump Media Group CRO Strategy, Inc., is focused on acquisition of CRO, the native token of the Cronos ecosystem. 

As per the official release, the trio will be founding partners in the treasury and they will purchase $1 billion worth of CRO at market price, roughly 6.31 billion tokens, representing nearly 19% of its total market supply. Additionally, the treasury will use $200 million in cash and $220 million cash-in mandatory exercise warrants, with an additional $5 billion equity line of credit from an affiliate of Yorkville, YA II PN, Ltd. 

The move will make Trump Media Group CRO Strategy, Inc., the first and largest publicly traded CRO treasury company. Beside the deal, YA II PN, Ltd. also entered into a backstop agreement to purchase Class A ordinary shares of Yorkville Acquisition Corp. 

“Financial markets are becoming increasingly digital every day, and companies of all sizes and sectors are strategically planning for the future by establishing digital asset treasuries anchored by assets that have created a comprehensive value proposition and are poised for even greater utility,” said Devin Nunes, Chairman and CEO of Trump Media & Technology Group.

CRO Token Spikes 25% 

Following the announcement, CRO token price surged by staggering 23%, surging from $0.1623 to $0.1996 in hours. Although it is nearly 80% away from the previous all-time high of $0.9698, marked in November 2021. 

So far the Trump Media Group CRO Strategy, Inc. is the largest altcoin strategy in existence compared to CRO’s market cap. At the time of writing, the total market capitalization for Cronos (CRO) token sits at $6.57 billion–as per CoinMarketCap data. 

Altcoin Treasury Trend Accelerates

While the Ethereum (ETH) primitive ruled the crypto market in the first half of 2025, the altcoin treasury trend is now taking the central stage with various publicly traded companies increasingly adopting altcoins like Ethereum and Solana (SOL) as treasury assets. The trend is inspired by MicroStrategy‘s Bitcoin strategy and SharpLink Gaming’s pivot to ETH.

Also read: Altcoins Make Bitcoin Growth Stronger: Tim Draper

Leituras Relacionadas

TRON Nile Testnet Deploys Quantum-Resistant Signature Cryptography

TRON's Nile testnet has deployed an upgrade implementing quantum-resistant signature cryptography, a proactive step to secure its ledger against potential future decryption threats from quantum computing. This development, confirmed via official sources like nileex.io and github.com, represents a notable Layer 1 security enhancement. The report emphasizes its relevance within the current market focus on stablecoins. Crucially, the upgrade is currently active only on the testnet, not the TRON mainnet. While providing a verified data point for the market to weigh, the article cautions that this single development should be considered alongside broader market factors and does not guarantee any specific price action. It stands as a snapshot of ongoing protocol development.

bitcoinistHá 28m

TRON Nile Testnet Deploys Quantum-Resistant Signature Cryptography

bitcoinistHá 28m

BIS Report Compliance Observations: The True Risks of Stablecoins Go Beyond 'De-pegging'

The BIS report, "Anchoring trust in money: innovation beyond stablecoins," highlights that the primary risks of stablecoins extend beyond potential de-pegging. It argues that the core challenge is whether stablecoins can be integrated into a financial system that is identifiable, monitorable, accountable, and regulatable. While acknowledging efficiency gains like faster payments and programmability, BIS emphasizes that money requires an institutional framework—including legal certainty, liquidity support, and financial integrity controls—which many stablecoins currently lack. The report details compliance risks, noting that while blockchain transactions are transparent, address visibility does not equate to identity or purpose clarity. This creates a systemic risk as pseudonymity, non-custodial wallets, and cross-chain bridges can undermine AML/CFT controls. Furthermore, these risks can spill over into the traditional financial system through on- and off-ramps. The future direction, per BIS, is not to prohibit innovation but to embed regulatory rules—such as identity verification and transaction screening—directly into the technological infrastructure of tokenized finance. The key takeaway for compliance is that any new financial instrument must clearly address questions of customer identification, transaction monitoring, accountability, and cross-border rule consistency to be viable as a mainstream payment tool.

marsbitHá 57m

BIS Report Compliance Observations: The True Risks of Stablecoins Go Beyond 'De-pegging'

marsbitHá 57m

When US Giants Collectively "Defect" to Chinese AI Models

When Silicon Valley Giants Turn to Chinese AI Models to Cut Costs A surprising trend is emerging: major U.S. tech companies are significantly reducing AI costs by switching to Chinese models. Coinbase, the largest U.S. cryptocurrency exchange, reportedly halved its AI spending after migrating to China's GLM-5.2 and Kimi 2.7 models, despite increasing usage. They achieved this through a sophisticated three-part strategy: implementing an automatic routing system to select the most cost-effective model per task, boosting cache hit rates from 5% to 60% to reuse computations, and employing "context engineering" to provide AI with more precise, less cluttered information. They are not alone. AI startup Lindy switched from Claude to DeepSeek, saving millions, while Snowflake's tests found GLM-5.2 solved 66% of coding tasks compared to Claude Opus's 67%—but at a fraction of the cost (output pricing is 5-7 times lower). While the top Western models may offer slightly better stability, the massive price differential is leading many businesses to reconsider their value proposition. This shift signals a deeper change in the AI industry, moving beyond pure performance benchmarks to a fierce cost competition. As pressure mounts, even OpenAI and Anthropic have begun slashing prices. For users, this means more choices, lower costs, and a crucial lesson: using multiple models based on task complexity, optimizing with caching, and keeping contexts lean are now key to leveraging AI efficiently and affordably.

marsbitHá 1h

When US Giants Collectively "Defect" to Chinese AI Models

marsbitHá 1h

BIS Report Compliance Watch: The Real Risks of Stablecoins Are Not Just 'De-pegging'

BIS Report Compliance Observations: The real risks of stablecoins go beyond "depegging" The BIS report "Anchoring trust in money: innovation beyond stablecoins" argues that while stablecoins and tokenization offer efficiency gains, their primary risk lies in fitting into an identifiable, monitorable, accountable, and regulatable financial system. Money's trust stems not just from technology but from institutional arrangements: a common unit of account, guaranteed redemption at par, liquidity support, regulatory frameworks, and financial integrity requirements. Stablecoins, operating on permissionless blockchains with pseudo-anonymity and non-custodial wallets, create systemic compliance gaps: unclear customer identity, incomplete fund origins, unexplained transaction purposes, fragmented cross-chain paths, and ambiguous liability. On-chain transparency does not equal compliance transparency. Public addresses don't reveal identity or intent. While blockchain analytics aid law enforcement, they cannot replace routine, large-scale AML/CFT controls. Effective compliance requires a closed-loop process encompassing customer onboarding, transaction monitoring, investigation, reporting, and audit. Stablecoin risks are not confined to the blockchain; they re-enter the traditional financial system via on/off-ramps, exchanges, and payment institutions. This forces banks to monitor client accounts for activity linked to virtual assets. The future direction is not to prohibit innovation but to embed rules into the technology. Tokenized finance should integrate with the existing two-tier monetary system, embedding compliance—like customer identification, pre-transaction screening, and auditable data trails—directly into the transaction flow. For compliance professionals, the key takeaway is that any new financial instrument must answer core questions: Who identifies the customer? Who monitors transactions? Who handles exceptions? Who is liable? Compliance is not the antithesis of innovation but the essential infrastructure for its sustainable growth.

链捕手Há 1h

BIS Report Compliance Watch: The Real Risks of Stablecoins Are Not Just 'De-pegging'

链捕手Há 1h

When American Giants 'Defect' to Chinese AI Models

Summary: The trend of major U.S. technology firms adopting more cost-effective Chinese AI models is gaining momentum. A prime example is Coinbase, the largest U.S. cryptocurrency exchange, which reportedly halved its AI expenditure by switching to Chinese models GLM-5.2 and Kimi 2.7, while its usage volume increased. This was achieved through a sophisticated cost-saving system featuring intelligent model routing (selecting the most suitable model per task), dramatically improving cache hit rates from 5% to 60%, and implementing "Context Engineering" to streamline prompts. This shift is not isolated. Other companies like the AI startup Lindy and data cloud firm Snowflake are making similar moves, drawn by the significant price disparity. For instance, GLM-5.2 costs $1.40/$4.40 per million tokens (input/output), compared to $5/$25 for Claude Opus 4.7. While top Western models may offer slightly higher stability or speed in complex tasks, the performance gap is narrowing, making the price difference harder to justify for many enterprise use cases. The implications are significant for both businesses and individual users. It highlights the importance of a multi-model strategy based on task requirements, the value of caching and reusing outputs, and the effectiveness of providing concise context. Ultimately, this migration signals a potential reshaping of the AI industry's pricing model, moving competition from pure performance benchmarks to practical cost-effectiveness, with increased choice and downward price pressure benefiting end-users.

链捕手Há 1h

When American Giants 'Defect' to Chinese AI Models

链捕手Há 1h

Trading

Spot
活动图片

Categorias popularesright-arrow

Etiquetas Popularesright-arrow