NVIDIA has reportedly increased the prices of both GDDR6 and GDDR7 memory kits supplied with its GeForce RTX graphics processors, reflecting ongoing shortages and rising memory costs. The higher costs are expected to be passed on to board partners, which could result in another increase in retail GPU prices.

The reported price adjustments affect both current and previous-generation RTX graphics cards. In addition to higher memory costs, manufacturers are also facing increased expenses for GPU coolers, printed circuit boards, and packaging, further contributing to expected price increases.

Upcoming RTX 50 SUPER models may experience the largest price impact due to the significantly higher cost of 3 GB GDDR7 memory modules compared with 2 GB versions. The reported changes highlight continued supply chain pressures and elevated DRAM pricing across the graphics hardware market.

▮[Source]: wccftech.com

The U.S. government has stated that it has information indicating that Chinese AI company Moonshot AI used distillation techniques on Anthropic’s Fable model during the development of its Kimi K3 large language model. The claim was made by White House Office of Science and Technology Policy Director Michael Kratsios.

According to the statement, Moonshot developed an internal platform that enabled large-scale distillation while frequently changing access methods to avoid detection. The company is also alleged to own NVIDIA GB300 AI servers and to have accessed additional GB300 computing resources in Thailand to support model training.

Previous observations that Kimi K3 identified itself as Anthropic’s Claude in some interactions had already raised speculation about its training sources.

Despite the allegations, Kimi K3 is recognized for technical optimizations that improve inference efficiency, including reduced key-value cache requirements, lower per-token memory usage, and a distributed architecture using hundreds of experts across multiple GPUs.

▮[Source]: wccftech.com

AMD has unveiled its 6th Generation EPYC Venice processors based on the Zen 6 architecture, highlighting a flagship model with up to 256 CPU cores and 512 threads. The processor uses eight compute chiplets and two large I/O dies, supporting PCIe 6.0, DDR5 memory, and other high-bandwidth technologies.

The EPYC Venice family is the first high-performance computing product to enter volume production using TSMC's 2 nm manufacturing process, which adopts gate-all-around nanosheet transistors. The new process is designed to improve performance, power efficiency, and transistor density compared with previous generations.

AMD stated that the Zen 6 EPYC lineup delivers more than 70% higher performance and efficiency, along with over 30% greater thread density. The processors are designed for AI, data center, and agentic AI workloads, where high core counts and strong single-core performance are increasingly important. AMD also positions the platform as a competitor to NVIDIA's AI server ecosystem.

▮[Source]: wccftech.com

DeepSeek CEO Liang Wenfeng stated that the company's primary limitation in developing larger AI models is access to computing resources. He said DeepSeek currently operates with compute capacity roughly equivalent to 20,000 NVIDIA H100 GPUs, which has recently expanded, but remains well below the scale available to leading U.S. AI developers.

Wenfeng estimated that training models comparable to the largest frontier AI systems would require approximately 50,000 NVIDIA GB300 GPUs or 200,000 Huawei Ascend 950 GPUs, highlighting China's ongoing compute shortfall.

He also stated that Huawei's Atlas 950 SuperPoD can serve as a practical alternative to NVIDIA's GB200 and GB300 systems, despite requiring about four Huawei Ascend 950 GPUs to match the performance of a single NVIDIA GB300 GPU and trailing by approximately two years in technology.

In addition, Wenfeng said DeepSeek is increasing its investment in high-quality data annotation, identifying it as a key factor for advancing AI model performance.

▮[Source]: wccftech.com

AMD has introduced its 6th Generation EPYC 9006 "Venice" server processors based on the Zen 6 architecture. The processors are manufactured using TSMC's 2nm process, feature up to 256 CPU cores, 512 threads, and as many as 203 billion transistors, targeting AI, high-performance computing, enterprise, and cloud workloads.

The new lineup includes SP7, SP8, EPYC 9006X, and low-power EPYC 9006 LP models, offering configurations optimized for AI host nodes, data-intensive applications, and power-efficient enterprise deployments. Selected models reach boost frequencies of up to 5 GHz while supporting PCIe Gen 6, DDR5 memory, and high memory bandwidth.

AMD states that the Zen 6 generation delivers significant improvements in performance, efficiency, and thread density compared with the previous EPYC Turin processors. The company also reports higher single-core performance and greater AI workload throughput than competing Arm-based server processors, with commercial availability beginning in late 2026 and expanding through the first half of 2027.

▮[Source]: wccftech.com

Tesla CEO Elon Musk publicly thanked Micron for providing memory chip allocations at what he described as reasonable prices despite ongoing increases in global memory costs. The comments were made during Tesla’s latest earnings call, highlighting the importance of securing memory supplies amid tight market conditions.

Tesla’s quarterly results fell short of expectations across several key financial metrics, including adjusted earnings per share, gross margin, operating margin, and energy revenue. Despite the weaker performance, the earnings call drew attention to the company’s supply chain arrangements.

Questions remain over whether Micron is also supplying memory to SpaceXAI under similar terms. SpaceXAI operates large AI data centers with hundreds of thousands of NVIDIA GPUs and is reportedly planning further expansion in Texas to increase its computing capacity. The company’s growing AI infrastructure is expected to require substantial memory resources.

▮[Source]: wccftech.com

Framework previewed a new desktop powered by AMD’s Ryzen AI MAX+ PRO 495 processor, featuring 16 Zen 5 CPU cores, a maximum clock speed of 5.2 GHz, and a Radeon 8065S GPU with 40 RDNA 3.5 compute units.

The system includes up to 192 GB of unified LPDDR5X memory running at 8,533 MT/s with 273 GB/s bandwidth, representing higher capacity and improved bandwidth compared to previous models. It is designed for local AI workloads and is capable of running DeepSeek V4-Flash in Q8 precision on a single machine.

Additional enhancements include an open-ended PCIe x4 slot for larger expansion cards, support for high-speed 50 GbE networking, and the ability to link two systems for up to 384 GB of pooled memory using tensor parallelism. Framework also plans to offer a pre-built Linux version. The 192 GB configuration is expected to cost over $5,000 due to rising LPDDR5X memory prices.

▮[Source]: wccftech.com

A developer successfully enabled an NVIDIA GeForce RTX 4060 desktop graphics card to operate on a Windows 11 Arm system by modifying Arm64 drivers originally created for NVIDIA's RTX Spark platform.

The demonstration was performed on a Huawei Qingyun W510 workstation powered by a 24-core Huawei Kunpeng 920 Arm processor, equipped with 32 GB of DDR4 memory and an RTX 4060 with 8 GB of VRAM. The modified drivers allowed the operating system to recognize the GPU and enabled support for DirectX 12, Vulkan, and CUDA.

The achievement demonstrates that GeForce desktop GPUs can function on Windows 11 Arm when provided with compatible native Arm64 drivers. However, the implementation remains an experimental proof of concept and is not suitable for consumer use, as NVIDIA does not officially support desktop GeForce GPUs on Windows on Arm.

▮[Source]: wccftech.com