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According to official news, the Circle Cross-Chain Transfer Protocol (CCTP) now supports a fast transfer prepayment fee feature. Previously, the protocol fee would be directly deducted from the USDC transfer amount on the target chain; with this update, developers can pre-quote and collect fees using the native Gas token or USDC from the source chain before executing the transfer, thereby simplifying the fee handling for cross-chain transfers and ensuring that users receive the expected amount of USDC.It is reported that the prepayment fee mechanism mainly improves the predictability of fees in cross-chain applications. Users do not have to bear the reduction in the actual amount received due to additional deductions on the target chain; at the same time, the CCTP Quote API can uniformly calculate fees for different supported chains and integrate Fast Transfer and Forwarding fees into a single quote, so developers do not need to build systems to separately calculate multiple protocol fees. In addition, fees can be paid directly using the native token of the source chain, which will not reduce or affect the actual transferred USDC balance.Currently, the prepayment fee feature supports USDC transfers on all EVM chains covered by CCTP, but it does not support transfers initiated from Solana; transfers to Solana are still supported. Developers can obtain specific fee quotes through the Quote API and integrate this feature, and relevant developers can refer to the CCTP official documentation to build a more predictable cross-chain USDC transfer process.

According to a post by X platform user "Yongchutafi" (@xhyctf) on September 8, DeepSeek may launch a new model V4.1 Flash.

According to Bloomberg, ByteDance is preparing to launch an artificial intelligence model for real-time spatial video generation, with applications covering fields such as robotics and autonomous systems, and will compete with companies like Meta and Alphabet.Insiders say that ByteDance founder Zhang Yiming is personally overseeing the development of the model, coordinating multiple business departments within the company, and investing in artificial intelligence resources and computing power support. The model may be released as early as next month, but the specific timing is still subject to change.

Goldman Sachs significantly raised its industry forecast in the latest global optical module report, expecting the global optical module market size to reach approximately $67.7 billion, $131.4 billion, and $148.5 billion in 2026, 2027, and 2028 respectively, an increase of 33%, 81%, and 115% compared to previous forecasts.Goldman Sachs believes that this round of upward revision is not solely due to the increase in the number of AI servers; more importantly, the architecture of AI servers is continuously migrating towards high-speed networks, coupled with the increase in the number of optical modules required for a single GPU or ASIC chip, driving rapid growth in demand for 800G, 1.6T, and even 3.2T.

The Sun Wukong ecosystem will hold a roundtable discussion at X Space on September 8th at 8 PM, with the theme "GPT-6, Claude, Grok taking turns to upgrade, the AI model war has entered the second half."This event will focus on the shift in industry competition amid the convergence of leading large model capabilities, and will delve into the evolution of true industry barriers from model parameters to underlying computing power scheduling, multi-model API routing efficiency, and the infrastructure supporting Agent automated execution.

According to the latest data from OpenRouter reported by the Daily Economic News, the total global invocation of AI large models last week (from August 31 to September 6) reached 115 trillion tokens, a month-on-month increase of 1.77%. Among them, the weekly invocation of China's AI large models reached 56.72 trillion tokens, a month-on-month increase of 2.83%, surpassing the United States (16.54 trillion tokens, a month-on-month decrease of 3.1%) for nineteen consecutive weeks, ranking first in the world.Among the top five global invocation volumes, four are Chinese models. Tencent's Hyper Yuan Hy4 preview ranks first with 14.7 trillion tokens, a month-on-month increase of 379%; GPT-5.6 Luna ranks second with 12.9 trillion tokens; Zhiyu GLM-5.3 Flash rises to third with 12.4 trillion tokens; DeepSeek-V4-Flash's official and preview versions rank fourth and fifth, respectively.MiniMax M3 returns to the list after nearly a month, ranking sixth, and has become the foundational base for Saudi HUMAIN's Arabic large model. In addition, Xiaomi MiMo-V2.5 and Gemini 3.7 Flash fell out of the list this week.

BNB Chain Chief Growth Officer Nina Rong commented on "the debate between Arbitrum founder Steven Goldfeder and Solana co-founder Toly regarding the Robinhood Chain fee model": "Continuing to push Gas fees lower is no longer the highest priority for the blockchain industry. The real priority for all public chains today is to find sustainable business models and reinvest the profits into technology and growth. This business model can be based on Gas fees, revenue sharing, or other forms of business collaboration. Over the past five years, the impression of blockchain foundations has mostly been two things: one is issuing grants and making investments; the other is reducing Gas fees. If we want to continue for another five years, blockchain companies must have a solid business structure."

The founder of Arbitrum, Steven Goldfeder, and Solana co-founder, Toly, engaged in a debate over the fee model of Robinhood Chain. Toly claimed that the 10% revenue share paid to Arbitrum by Robinhood Chain is sufficient to cover four times the transaction fees on the Solana chain, suggesting that if deployed on Solana, user gas fees could significantly decrease. In response, Goldfeder stated that Robinhood could retain about 90% of gas revenue under the Arbitrum architecture, thus choosing Arbitrum to "be the landlord, not the tenant."Toly countered that Robinhood could charge fees at the application front end while utilizing a lower-cost underlying network; Goldfeder, however, indicated that a large amount of on-chain activity does not go through the Robinhood front end, and if it were merely a "tenant" of the underlying network, Robinhood would not be able to capture the revenue generated from these peripheral activities.According to market news, Robinhood evaluated both Solana and Arbitrum during the product initiation phase and ultimately chose Arbitrum, which allows for independent chain deployment.

According to The Defiant, the dispute between AMC Entertainment CEO Adam Aron and Robinhood over tokenized AMC stock has escalated into a debate among tokenized stock issuers about which model should become the industry standard.Gabriel Otte, co-founder of Dinari, criticized Robinhood's synthetic tokens with Ondo as "worse for end investors than regular stocks," while Uniswap founder Hayden Adams compared it to early stablecoins, stating that it meets users' demands for programmability and 24/7 trading.Currently, three models are competing in the $2.91 billion tokenized stock market: Robinhood's stock tokens are debt securities issued by a Jersey entity, available only to non-U.S. persons; Ondo, xStocks, and Dinari hold the underlying stocks through regulated intermediaries and pass on economic benefits; Securitize and Superstate directly put company-registered stocks on-chain. The U.S. SEC's Division of Corporation Finance has legally defined the three models as of January 28. Data from rwa.xyz shows that the total scale of tokenized stocks reaches $2.91 billion, with a 14.4% growth over 30 days, and Ondo leads with $869.6 million.Securitize CEO Carlos Domingo also supports Aron's position, stating that he does not wish for others to create offshore derivatives of company stocks. Brian Huang, co-founder of Glider, believes that the trading venue is more important than the packaging format, as AMMs cannot guarantee users the best execution.

GLM-5.3-Flash has become the most frequently used and popular model on the B.AI platform, with a cumulative token throughput exceeding 2.41 trillion.As the first native multimodal model in the GLM-5 series, GLM-5.3-Flash features a total of 320 billion parameters and 18 billion active parameters, employing a hybrid architecture that combines sparse and linear attention, supporting 1 million ultra-long contexts, while ensuring rapid response, powerful reasoning, and high cost-effectiveness.Starting today, developers can still call this model for free through the B.AI platform, covering diverse scenarios such as high-frequency APIs, code writing, complex agents, and ultra-long document processing.

According to Digital Asset, the South Korean Financial Services Commission has announced plans to advance a tokenization model for listed stocks centered around the Korea Exchange (KRX), referencing pilot programs from the New York Stock Exchange and NASDAQ. Non-listed stocks will be advanced for tokenization through a trust method.The Financial Services Commission has released a three-phase roadmap for the tokenization of standardized assets. The first phase will launch in February 2027 when the token securities law is implemented, targeting tokenization of private money market funds, private corporate bonds, and non-listed stocks, limited to institutional investors. The second phase will expand the scope to public offerings. The third phase will promote "on-chain settlement," meaning that both securities and settlement methods will complete payments and settlements on the blockchain. The Financial Services Commission stated that on-chain settlement will be officially advanced after stablecoin legislation.

On Thursday, the Saudi Arabian artificial intelligence company Humain launched a national AI platform and introduced the Arabic model humain-m3. This model is based on the open-source model M3 from the Chinese laboratory MiniMax Group Inc. Humain is supported by the Public Investment Fund and has invested in data centers and chips to enhance Saudi Arabia's competitiveness in the global AI field.Humain stated that its commissioning of the model aims to strengthen the Arabic AI ecosystem while contributing to the global advancement of cutting-edge intelligence. The company thus joins the ranks of nations seeking to strengthen control over this increasingly important technology.

OpenAI released a video on X, previewing the upcoming release of the Astra model (the video content switches between ASTRA and A6TRA), and the model name may be GPT-6-Astra.

The official Chinese version of the "2026 Artificial Intelligence Index Report" from Stanford University's Human-Centered Artificial Intelligence Institute (HAI) was officially released today. The report points out that artificial intelligence has moved beyond a mere competition of model capabilities and is deepening into systemic changes at the levels of infrastructure, organizational processes, and institutions.Currently, the leading models worldwide are performing close to 100% human level on the software engineering benchmark SWE-bench; the success rate of agents in real computing environments has surged from 12% to 66%, with AI evolving from "generating information" to "executing tasks." The gap between top models in China and the U.S. has narrowed to 2.7%, with leading models from both sides having exchanged positions multiple times.In addition, physical infrastructure has become a core constraint on AI development. The global AI data center power capacity has reached 29.6 gigawatts, and chips, energy, and water resources are becoming key strategic bottlenecks for AI development.

Tether is expanding its business beyond stablecoins by launching an open-source AI translation model that can run offline on smartphones and laptops.These models support 19 African languages, and Tether positions this technology for use in education, healthcare, and other areas with limited internet access.

On September 2, B.AI announced that its Responses API is now integrated with the DeepSeek series of models. Developers can use the B.AI API Key to call the DeepSeek series of models supported by the B.AI platform in the Codex client.Previously, B.AI had supported calling the GPT series of models through Codex. After configuring the API Key and Base URL, developers can switch between DeepSeek and GPT for scenarios such as code generation, understanding, debugging, refactoring, and development collaboration.

OpenAI stated that its upcoming Astra model can autonomously discover previously unknown software vulnerabilities and convert them into usable attack vectors without human intervention, making it the company's first model to reach the "Critical" cybersecurity capability level threshold. In a blog post released on Tuesday, OpenAI mentioned that according to its Preparedness Framework, reaching this level means the model can discover zero-day vulnerabilities and develop usable exploit code in hardened real systems without human involvement, or design and execute attacks based solely on a high-level objective.In testing, Astra achieved a 100% score in benchmark tests for developing exploit code based on known vulnerabilities and discovered two previously unknown vulnerabilities in another internal test. Additionally, the model successfully broke through a hardened browser sandbox and executed commands on the host machine, while gaining root access by exploiting multiple weaknesses in the operating system. OpenAI stated that it has delayed some of Astra's development progress to enhance security measures and plans to make its advanced cybersecurity capabilities available only to selected testers.This capability is particularly relevant to the cryptocurrency industry, as software vulnerabilities can be converted into financial losses within minutes. CoinDesk reported in June that increasingly powerful AI models can compress the process of searching code, discovering misconfigurations, and assembling attacks from days or weeks to machine speed. Security researchers noted at the time that the significant change was not the emergence of new categories of attacks, but rather the dramatically increased speed at which existing vulnerabilities are discovered and exploited.

Robonomics author FD published the China Open-Source LLM Tracker on September 1, 2026, stating that the total ARR of China's open-source large models is approximately $10-15 billion, with core LLM revenue around $6-8 billion after excluding ByteDance / Seedance. Growth has not relied on price wars; after DeepSeek raised prices by about 3-12 times, usage still increased, and the average price of the Zhipu API rose by 101% while token usage exceeded 40 times within the year. The best estimate for overseas revenue is approximately $2 billion.Zhipu MaaS ARR increased from about $250 million in March to an annualized monthly rate of about $1.6 billion in August, with a weekly annualized rate of $2 billion. August revenue has already surpassed its API revenue for the first half of the year; the API gross margin is 24.6%, and inference costs per token decreased by 80%. MiniMax ARR rose from about $100 million in December 2025 to over $800 million in annualized weekly revenue by August 2026, with B2B accounting for about 80%. Kimi ARR increased from about $100 million in March to about $300 million by mid-June. DeepSeek's revenue from January to July was approximately $70 million, with the latest ARR estimated at about $1.2 billion.ByteDance's annualized AI revenue is approximately $4 billion, of which Seedance accounts for about $2 billion.