route

WORLD3 today announced the official launch of its decentralized AI routing network RouterLink, enabling the permanent domain routerlink.ai. This official version brings three core upgrades compared to the previous Alpha stage: complete Web2 payment support (Stripe credit card/debit card/Apple Pay/Google Pay), direct connection to over 60 cutting-edge purebred flagship models (without quantization, without distillation), and official production-level endorsements from three major cloud providers: AWS, Microsoft Azure, and Google Cloud.WORLD3 disclosed that the RouterLink network currently supports over 68 models, covering more than 20 providers, with uptime locked at 99.9%, and daily settlement flow exceeding $1.5 million $WAI. The launched purebred flagship models include Claude Opus 4.7, GPT-5.5, Gemini 3.1 Pro Preview, DeepSeek V4 Pro, Grok 4.3, Qwen3-Max, Llama 4 Maverick, Kimi K2.6, GLM 5.1, MiniMax M2.7, etc., all provided at full specifications. The cumulative $450K quota from the three major cloud collaborations has been fully utilized — including the public inclusion of the AWS Customer Case Study, Microsoft for Startups Level 4 (highest level) + $300K AI Grants, and direct connection to Google Cloud Vertex AI.WORLD3 stated that this official launch also opens up the enterprise procurement channel: Stripe payments and $WAI on-chain payments run in parallel, allowing developers to access the complete catalog of 68 models within 60 seconds after registering their email and recharging with a credit card. The subsequent roadmap includes the RouterLink mainnet, GPU computing power market, an Agent skill market linked with TapClaw, and an enterprise version SLA service that is already in pilot with some clients.

According to CoinDesk, Coinbase has revealed that it has integrated the trading protocol DFlow as the main trading router for its Solana ecosystem, supporting users in achieving native value exchange for spot and prediction markets on Solana.Coinbase stated that after introducing DFlow, the trading failure rate for its Solana products dropped from about 1/30 to approximately 1/250, an 8-fold decrease. At the same time, this solution has expanded the liquidity coverage, enabling small and mid-cap tokens that were previously unable to trade due to "lack of liquidity" to become tradable, and optimizing user transaction prices.

Gate announced the launch of the GateRouter enterprise account feature, enhancing enterprise-level management capabilities based on the existing AI model gateway, providing an integrated AI usage and governance solution for team and institutional users. GateRouter supports quick access to over 30 mainstream models such as GPT, Claude, DeepSeek, and Gemini through a single API, and automatically matches models based on task complexity. By intelligently routing and automatically selecting cost-effective models, GateRouter can help enterprises significantly reduce costs and achieve more efficient scalable applications.The launch of the GateRouter enterprise account feature optimizes three aspects: cost, permissions, and data. It achieves unified billing through a shared quota pool and controls budgets with a three-tier quota mechanism based on organization, members, and API Key; it supports up to 4 levels of organizational structure and a multi-role permission system for refined management; it also provides multi-dimensional statistics such as per capita usage, model distribution, and API Key, making AI usage traceable and analyzable. The overall design connects model invocation with organizational management, providing foundational support for the scalable implementation of AI within enterprises.

According to CoinDesk, researchers from the University of California, Santa Barbara, the University of California, San Diego, blockchain security company Fuzzland, and World Liberty Financial have jointly published a paper warning that "LLM routers"—intermediary services located between users and AI models—have become a significant security risk for crypto assets.The researchers found that 26 LLM routers are secretly injecting malicious tool calls and stealing user credentials, with one incident leading to the emptying of a customer's crypto wallet worth $500,000.Additionally, the researchers were able to control about 400 downstream hosts within hours by "polluting" the router ecosystem. Since sensitive data such as private keys and API credentials are often transmitted in plaintext through these routers, users are effectively exposing their assets to risk without their knowledge.The researchers pointed out that as McKinsey predicts AI agents will mediate $30 trillion to $50 trillion in global consumer spending by 2030, Binance founder Changpeng Zhao also predicts that the payment volume of AI agents will be a million times that of humans. The current infrastructure security is severely lagging behind the pace of industry development, and the risk of the "weakest link" could trigger a systemic chain crisis.

According to market news, researchers from the University of California recently disclosed that some third-party AI large language model (LLM) routers have security risks that could lead to the theft of cryptocurrency assets. The research shows that LLM routers, acting as API intermediaries, can read plaintext information, and some routers have been found to inject malicious code and steal credentials.The team tested 28 paid and 400 free routers, finding that 9 routers actively injected malicious code, 2 deployed evasion triggers, and 17 accessed Amazon Web Services credentials. Some routers even transferred ETH using the researchers' Ethereum private keys.The study pointed out that the malicious behavior of the routers is difficult to detect, and some AI agent frameworks' "YOLO mode" can automatically execute commands, increasing security risks. The research recommends that developers should not allow private keys or mnemonic phrases to be transmitted through AI agents and calls on AI companies to encrypt signatures in responses to enhance security.

According to Arkham data, at 19:54, 355.61 BTC (worth approximately $20,137,800) was transferred from one anonymous address (starting with bc1qmd...) to another anonymous address (starting with bc1qwpp...). Subsequently, that address transferred a portion of the BTC (55.61 BTC) to another anonymous address (starting with bc1qll...).

According to Arkham data, at 19:00, 354.99 BTC (worth approximately 23.8368 million USD) was transferred from one anonymous address (starting with 3Da3...) to another anonymous address (starting with bc1qr...).

According to Arkham data, at 14:40, 355.09 BTC (worth approximately 23.76 million USD) was transferred from one anonymous address (starting with bc1q08cyv...) to another anonymous address (starting with 3GcxuZnE...). Subsequently, that address transferred 355.07 BTC to another anonymous address (starting with bc1qq68v7...).

According to Arkham data, at 13:06, 355.1 BTC (worth approximately $23.7432 million) was transferred from one anonymous address (starting with 3GcVwL...) to another anonymous address (starting with bc1qaj...).

According to Arkham data, at 12:12, 355.11 BTC (worth approximately 23.73 million USD) was transferred from one anonymous address (starting with bc1q6m4c...) to another anonymous address (starting with bc1qlyt2...). Subsequently, that address transferred part of the BTC (355.11 BTC) to another anonymous address (starting with bc1qan3y...).

According to Arkham data, at 10:11, 355.12 BTC (worth approximately $23.7476 million) was transferred from one anonymous address (starting with 3MnhtmEtfR...) to another anonymous address (starting with 3NbTUU1HWD...). Subsequently, that address transferred 355.11 BTC to another anonymous address (starting with bc1qan93p95...).

According to Arkham data, at 09:32, 355.16 BTC (worth approximately 23.74 million USD) was transferred from one anonymous address (starting with bc1qpekw0...) to another anonymous address (starting with bc1qtx76...). Subsequently, that address transferred 355.14 BTC to another anonymous address (starting with bc1qn5q8...).

According to Arkham data, at 07:00, 355.19 BTC (worth approximately 23.76 million USD) was transferred from one anonymous address (starting with 3NcbM...) to another anonymous address (starting with bc1qdl0m...). Subsequently, that address transferred 355.19 BTC to another anonymous address (starting with bc1qgt0t...).

According to Arkham data, at 06:20, 355.21 BTC (worth approximately 23.753 million USD) was transferred from one anonymous address (starting with bc1q8u2kh...) to another anonymous address (starting with 3NcbM5L...).

According to Arkham data, at 06:08, 355.21 BTC (worth approximately 23.76 million USD) was transferred from one anonymous address (starting with bc1qcrm2d03l...) to another anonymous address (starting with bc1q8u2khcga...).

According to Arkham data, at 05:38, 355.32 BTC (worth approximately 23.77 million USD) was transferred from one anonymous address (starting with bc1qgpw...) to another anonymous address (starting with bc1q393...).

According to Arkham data, at 05:02, 355.32 BTC (worth approximately $23.7474 million) was transferred from one anonymous address (starting with bc1q263x...) to another anonymous address (starting with bc1q9q5k...).

According to Arkham data, at 19:04, 1756.4 BTC (worth approximately $1.173 billion) was transferred from one anonymous address (starting with bc1qcdq4...) to another anonymous address (starting with bc1q3gw0...). Subsequently, this address transferred part of the BTC to two addresses on Bybit.

According to Arkham data, at 17:11, 355.5 BTC (worth approximately 23.78 million USD) was transferred from one anonymous address (starting with 3JqRBU...) to another anonymous address (starting with bc1qt3v2...).

According to Arkham data, at 17:03, 355.5 BTC (worth approximately 23.81 million USD) was transferred from one anonymous address (starting with bc1q7a...) to another anonymous address (starting with 3JqRB...).