On June 14th local time, Nvidia opened up the Nemotron-4 340B (340 billion parameter) series model.
According to NVIDIA, developers can use this series of models to generate synthetic data for training Large Language Models (LLMs) for commercial applications in healthcare, finance, manufacturing, retail, and other industries. The Nemotron-4 340B includes the base model, instruction model, and reward model. Nvidia used 9 trillion tokens (text units) for training.
In common sense reasoning tasks such as ARC-c, MMLU, and BBH benchmark tests, Nemotron-4 340B-Base can be comparable to Llama-3 70B, Mixture 8x22B, and Qwen-2 72B models.
As of the close of the US stock market on Friday, Nvidia, ranked first in trading volume, rose 1.75%, reaching a new historical high with a trading volume of $40.723 billion and a market value of $3.244 trillion. Nvidia has risen 9.1% this week, marking the eighth consecutive week of gains.
Huatai Securities released a report stating that Nvidia will spin off its stocks in a "one to ten" manner to increase liquidity, which will take effect after the market closes last Friday (7th). The company's last announcement of "one spin off and four spin off" was in 2021. From announcement to execution (May 21 to July 19 of the same year), three months later (July 19 to October 20 of the same year), and six months later (July 19, 2021 to January 20, 2022), the stock price rose by 25%, 18%, and 29%, respectively.
As a leader in the AI industry, Nvidia's performance this year has been impressive. As of now, Nvidia's stock price has accumulated an increase of over 150% this year, far exceeding the growth of the Nasdaq index during the same period.
The soaring stock price of Nvidia is driven by positive factors such as product upgrades and outstanding performance. Nvidia CEO Huang Renxun previously announced that the company plans to launch a high-performance version of Blackwell chips, Blackwell Ultra, in 2025, and a new AI chip platform, Rubin, in 2026. Rubin's Ultra version will debut in 2027.
In addition, the recently released first quarter financial report showed that Nvidia's adjusted earnings per share reached $6.12, with a revenue of $26 billion, an increase of 461% and 262% respectively compared to the same period last year. Among them, the revenue of data center business increased by 427% year-on-year, reaching 22.6 billion US dollars, accounting for 86% of the company's total revenue.
Tesla CEO Musk announced on social media on June 3rd that his artificial intelligence startup xAI will purchase 300000 Nvidia B200 AI chips. "The next important step may be to have about 300000 B200 chips equipped with CX8 networks next summer," Musk said.
According to the Daily Economic News, for Nvidia, in the short term, technology companies need to continuously invest computing power and resources, and chip demand continues to rise. According to MarketWatch, Nvidia GPUs are essentially the new gold/oil in the technology sector, and may become the world's first stock with a market value of $4 trillion.
But beyond the optimistic voices, there are also analyses that suggest that neither closed source models such as ChatGPT nor open source models under Meta and Google have yet to explore a stable commercialization path. From the dimensions of price and market business model, as well as the gathering of technology giants to develop their own chips, Nvidia's chip procurement in the future also presents uncertainty.
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