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Nvidia B300 Servers Hit $1 Million in China Amid US Export Crackdown

Nvidia’s advanced B300 AI servers are now reportedly selling for nearly $1 million each in China, almost double their U.S. price, as tighter American export restrictions and anti-smuggling enforcement create severe supply shortages. According to industry sources, the scarcity has transformed the B300 into one of China’s most expensive and sought-after AI computing assets.

The B300, equipped with eight GPUs and designed for high-performance AI inference, normally costs around $550,000 in the United States. In China, however, prices have surged to roughly 7 million yuan due to shrinking grey-market channels and rising demand from major Chinese technology firms racing to expand AI model deployment.

China’s growing need for AI infrastructure is accelerating the premium. Local firms are under pressure to secure hardware capable of efficiently processing tokens, a key monetization factor for generative AI systems. At the same time, many companies are cautious about directly owning restricted Nvidia systems because of potential exposure to U.S. sanctions.

The market disruption intensified after U.S. legal action against individuals tied to Nvidia partner Supermicro, further constraining unofficial supply routes. As a result, some Chinese companies are shifting from direct purchases to rentals, with monthly leasing costs reaching as high as 190,000 yuan.

This environment is also creating strategic opportunities for domestic rivals such as Huawei, which aims to capture market share as uncertainty around Nvidia’s H200 and B300 exports continues. Despite sanctions, Nvidia still holds a dominant position in China’s AI chip market, but prolonged restrictions may accelerate local alternatives and reshape competitive dynamics.

Nvidia Invests $2 Billion in Marvell to Strengthen AI Ecosystem

Nvidia has invested $2 billion in Marvell Technology as part of a broader strategy to maintain its central role in the rapidly evolving artificial intelligence infrastructure market.

The investment is designed to improve compatibility between Marvell’s semi-custom AI chips and Nvidia’s ecosystem, including its networking technologies and processors. As more companies explore custom silicon to reduce reliance on Nvidia’s high-cost GPUs, the move helps ensure those alternatives still integrate within Nvidia-dominated data center environments.

Marvell specializes in custom chip design and advanced networking solutions, particularly in optical interconnects and silicon photonics — technologies critical for high-speed, energy-efficient data transfer in large-scale AI systems.

Through this partnership, Marvell will provide custom silicon and networking components compatible with Nvidia’s NVLink Fusion architecture, while Nvidia will supply CPUs, network interface cards and interconnect technologies.

The deal reflects a strategic shift: rather than competing directly with all custom chip providers, Nvidia is positioning itself as the foundational platform enabling diverse AI hardware ecosystems.

Major technology firms such as Alphabet and Meta Platforms are expected to collectively spend over $600 billion on AI infrastructure this year, significantly boosting demand for advanced semiconductors and networking hardware.

Following the announcement, Marvell shares rose around 7%, while Nvidia also recorded gains, signaling strong investor confidence in the partnership.

SLB Expands Nvidia Partnership for AI Energy Infrastructure

SLB has expanded its partnership with Nvidia to develop artificial intelligence infrastructure and specialized models for the energy sector.

The collaboration builds on a long-standing relationship between the two companies and reflects increasing demand for AI-driven solutions across the energy industry. Companies are seeking to process vast amounts of geological, production and infrastructure data more efficiently to reduce costs, improve reliability and lower emissions.

Under the new agreement, SLB will serve as a design partner for modular AI data centers built on Nvidia technology. The partnership will also focus on creating an “AI Factory for Energy,” a platform designed to help energy producers and power companies convert complex operational data into actionable insights.

The move comes as oilfield service providers look to diversify their business models amid slowing drilling activity, shifting toward digital services and infrastructure linked to AI growth.

The expanded partnership highlights how artificial intelligence is becoming a central tool in transforming traditional industries, including energy, by improving efficiency and enabling more data-driven decision-making.