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Flash

Central Bank of Nigeria: Issued the "Regulations on the Operation of Non-Securities Virtual Assets," requiring a minimum paid-in capital of 15 billion Naira for foreign currency stablecoin issuers, and P2P transactions must verify BVN

According to the "Regulations for the Operations of Non-Security Virtual Assets in Nigeria" published by the Central Bank of Nigeria (CBN) on November 5, 2026, the CBN will regulate non-security virtual assets and stablecoins used for payment, settlement, and exchange purposes, while securities will still fall under the jurisdiction of the Securities and Exchange Commission (SEC).Foreign currency-pegged stablecoins (Class 2) must be issued by locally licensed entities in Nigeria, with a minimum paid-up capital of 15 billion Naira (approximately 11.16 million USD); the minimum for Naira-pegged Class 1 issuers is 10 billion Naira; entities providing other non-security virtual asset services must have at least 1 billion Naira in capital, and those already holding an SEC license cannot double count towards CBN capital requirements.P2P business facilitated by platforms must obtain special approval from the CBN, and before releasing or crediting regulated tokens, the names on the Naira payment accounts must be verified to match the Bank Verification Number (BVN). Categories such as algorithmic stablecoins are prohibited, and the boundaries of responsibilities between CBN and SEC are defined.

Baidu open-sourced Wenxin 5.5 Flash, with a total parameter of 280 billion

Baidu has open-sourced the ERNIE-5.5-Flash-Base model weights. Following the release of the ERNIE 4.5 series in June 2025, Baidu has once again open-sourced a large model with hundreds of billions of parameters after approximately 16 months, during which the ERNIE 5.0 and 5.1 versions were not open-sourced. The ERNIE 5.5 Flash focuses on inference efficiency, with a total of 280 billion parameters, activating only 14 billion parameters for each generated token, and using 33.5 trillion tokens for zero pre-training.This model supports a maximum inference context of 1 million tokens. Baidu has redesigned the long text processing mechanism, with 37 out of 43 layers compressing every 128 historical tokens into a single cache record, while the remaining 6 layers retain fine retrieval capabilities for the original content, reducing the memory and computational overhead of long text processing. The official evaluation was conducted in conjunction with DeepSeek-V4-Flash-Base, Tencent Hy3-preview-Base, and Xiaomi MiMo-V2.5-Base, ranking first in 24 out of 30 benchmark tests.What is being opened this time is a pure text Base model that has not undergone intermediate training or post-training, mainly for developers to continue domain fine-tuning, instruction training, and reinforcement learning. Baidu stated that the post-trained ERNIE 5.5 Flash will be released subsequently. The license is stricter than the previous generation; the ERNIE 4.5 used the Apache 2.0 protocol, while 5.5 Flash has switched to a custom license that does not authorize use in the European Union, the United Kingdom, and South Korea; for related products or services that have generated over 50 million dollars in revenue in the past 12 consecutive months, separate written authorization from Baidu must be obtained before commercial use.

first_img Baidu launched the model trading platform Ciyuan, gathering 42 large models

According to "Du Jia," Baidu recently launched an open model service platform called "Word Element Institute" aimed at developers, enterprise clients, and model suppliers. It is positioned as a matchmaking trading platform connecting model suppliers and consumers, gathering 42 large models, covering text and video models such as DeepSeek, Kimi, and Zhipu GLM. Developers can connect to the Word Element Institute API once to switch between models from multiple vendors and be billed based on usage.The same model can be accessed by multiple suppliers. The platform displays pricing, initial token latency, throughput speed, 7-day success rate, and historical call volume, and supports both OpenAI and Anthropic protocols. Taking DeepSeek-v4.1-flash as an example, the platform connects to 6 suppliers, marking the price savings ratio on the page, while also displaying context window, launch time, deployment region, and supplier credit evaluation.The platform ranking is based on real call data and can be viewed for the last 24 hours, last 7 days, and last 30 days. Screenshots show a total of 398 million calls in the last 7 days, with a total token volume of 51.336 trillion, involving 68 ranked model resources, and an average initial token latency of 290 milliseconds. DeepSeek-v4.1-flash ranks first in both call volume and token usage. Participating suppliers include Bochuan Technology, Infinite Mind, Star Hub Word Element, and Zhipu Original Factory, with the platform showcasing resources and supplier information through credit evaluations and blockchain proof.
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