AMD to Unveil Radeon RX 7900M Mobile Navi 31 GPU with 72 RDNA3 CUs on October 19


October 4, 2023

AMD to Unveil Radeon RX 7900M Mobile Navi 31 GPU with 72 RDNA3 CUs on October 19

Summary: AMD is reportedly set to unveil its powerful Radeon RX 7900M mobile GPU on October 19th, featuring 72 Compute Units, 4608 Stream Processors, and a 256-bit memory bus with 16GB of memory.

  • AMD is expected to introduce the Navi 31 GPU with up to 72 Compute Units for its high-end laptop GPUs
  • The RX 7900M is expected to boast 4608 Stream Processors, more than double the core count of the RX 7600M XT
  • The RX 7900M will feature a 256-bit memory bus, hinting at a 16GB memory configuration


Rumor has it that AMD is gearing up to unveil its highly anticipated RDNA3 mobile GPU, the Radeon RX 7900M. According to reports from Wccftech, the unveiling is expected to take place on October 19th, which coincides with the rumored release date of the Threadripper PRO 7000.

To provide some context, AMD has previously introduced mobile SKUs based on the Navi 33 architecture with the RX 7600M/S series. However, these GPUs have been relatively scarce in the gaming laptop market, as laptop manufacturers have favored the RTX 4050/4060 series from AMD’s competitor, nVidia. But now, it seems that AMD is ready to step up its game.

Initially, it was believed that AMD would introduce the Navi 32 GPU with up to 60 Compute Units for its high-end laptop GPUs, potentially in the RX 7800M series. However, recent reports suggest a shift in focus towards a more powerful Navi 31 architecture.

The upcoming RX 7900M is rumored to feature 72 Compute Units, indicating that it may not be based on the Navi 32 GPU. This aligns with previous rumors about a smaller Navi 31 package, similar to what we’ve seen in the RX 7900 GRE desktop model. The RX 7900M is expected to boast 4608 Stream Processors, more than double the core count of the RX 7600M XT.

While the 72 CU configuration represents a decrease compared to other high-end models like the RX 7900 GRE (80 CUs), RX 7900 XT (84 CUs), and RX 7900 XTX (96 CUs), this reduction seems to have been a strategic choice to keep the GPU’s Total Graphics Power (TGP) below 175 watts. This aligns with the power consumption limits for laptop GPUs.

In terms of memory, previous rumors suggest that the RX 7900M will feature a 256-bit memory bus, hinting at a 16GB memory configuration. This is a significant upgrade from the 8GB configuration found in the released RX 7000M cards, indicating that AMD is targeting the high-end market segment.

It’s worth noting that there is still a noticeable gap between the Navi 31/33 cards, suggesting that AMD may eventually introduce the Navi 32 architecture. Hopefully, the wait for its arrival won’t be too long.

Overall, the rumored AMD Radeon RX 7900M promises to bring substantial improvements to the mobile GPU market. With its increased Compute Units, higher core count, and upgraded memory configuration, it could offer a compelling alternative to Nvidia’s RTX series. We’ll have to wait for official confirmation from AMD to see if these rumors hold true.

(Source)

Background Information


About AMD: AMD, a large player in the semiconductor industry is known for its powerful processors and graphic solutions, AMD has consistently pushed the boundaries of performance, efficiency, and user experience. With a customer-centric approach, the company has cultivated a reputation for delivering high-performance solutions that cater to the needs of gamers, professionals, and general users. AMD's Ryzen series of processors have redefined the landscape of desktop and laptop computing, offering impressive multi-core performance and competitive pricing that has challenged the dominance of its competitors. Complementing its processor expertise, AMD's Radeon graphics cards have also earned accolades for their efficiency and exceptional graphical capabilities, making them a favored choice among gamers and content creators. The company's commitment to innovation and technology continues to shape the client computing landscape, providing users with powerful tools to fuel their digital endeavors.

AMD Website: https://www.amd.com/
AMD LinkedIn: https://www.linkedin.com/company/amd/

About nVidia: NVIDIA has firmly established itself as a leader in the realm of client computing, continuously pushing the boundaries of innovation in graphics and AI technologies. With a deep commitment to enhancing user experiences, NVIDIA's client computing business focuses on delivering solutions that power everything from gaming and creative workloads to enterprise applications. for its GeForce graphics cards, the company has redefined high-performance gaming, setting industry standards for realistic visuals, fluid frame rates, and immersive experiences. Complementing its gaming expertise, NVIDIA's Quadro and NVIDIA RTX graphics cards cater to professionals in design, content creation, and scientific fields, enabling real-time ray tracing and AI-driven workflows that elevate productivity and creativity to unprecedented heights. By seamlessly integrating graphics, AI, and software, NVIDIA continues to shape the landscape of client computing, fostering innovation and immersive interactions in a rapidly evolving digital world.

nVidia Website: https://www.nvidia.com
nVidia LinkedIn: https://www.linkedin.com/company/nvidia/

Technology Explained


Compute Units: Compute Units (CUs) are a type of processor technology used in the computer industry. They are designed to provide high-performance computing capabilities for a variety of applications. CUs are typically used in graphics processing units (GPUs) and are responsible for the majority of the processing power in modern gaming systems. CUs are also used in other areas of the computer industry, such as artificial intelligence, machine learning, and data analysis. CUs are designed to be highly efficient and can provide significant performance gains over traditional CPUs. They are also capable of handling multiple tasks simultaneously, making them ideal for applications that require high levels of parallel processing.


GPU: GPU stands for Graphics Processing Unit and is a specialized type of processor designed to handle graphics-intensive tasks. It is used in the computer industry to render images, videos, and 3D graphics. GPUs are used in gaming consoles, PCs, and mobile devices to provide a smooth and immersive gaming experience. They are also used in the medical field to create 3D models of organs and tissues, and in the automotive industry to create virtual prototypes of cars. GPUs are also used in the field of artificial intelligence to process large amounts of data and create complex models. GPUs are becoming increasingly important in the computer industry as they are able to process large amounts of data quickly and efficiently.





Radeon: AMD Radeon, a product line by Advanced Micro Devices (AMD), consists of graphics processing units (GPUs) recognized for their strong performance in gaming, content creation, and professional applications. Powered by innovative technologies like the RDNA architecture, Radeon GPUs deliver efficient and powerful graphics processing. The brand also supports features like FreeSync, enhancing visual fluidity and reducing screen tearing during gaming. Moreover, AMD Radeon GPUs embrace real-time ray tracing for heightened realism in lighting and reflections. With a balance between price and performance, Radeon competes with NVIDIA's GeForce graphics cards and remains a popular choice for a wide range of users.


TGP: TGP is the acronym for Total Graphic Power and is understood in only one way: the consumption of the GPU and its entire PCB, but without its cooling and lighting system. Formerly the TGP was called Total Board Power, but this parameter changed its definition for what was discussed just below. In other words, the TBP referred to the total peak consumption of the graphics card itself, with all its dissipation systems and LEDs included. Therefore, TGP has ended up being more specific, being a value that makes more reference to the card itself.



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