GIGABYTE Launches AMD Radeon PRO W7800 AI TOP 48G Graphics Card
James Cusworth / 1 month ago
GIGABYTE has just unleashed its latest powerhouse for workstation professionals and AI developers: the AMD Radeon PRO W7800 AI TOP 48G graphics card. This beastly GPU boasts AMD’s cutting-edge RDNA 3 architecture and a massive 48GB of GDDR6 memory, dwarfing its predecessor and promising unparalleled performance for complex design, rendering, and AI model training tasks.
Radeon PRO W7800
Crafted with premium-grade components, the new GIGABYTE professional graphics cards deliver incredible stability and endurance. With up to 48 GB of GDDR6 memory per card, users can achieve a memory capacity of up to 192 GB in a system with four cards installed. Additionally, ECC memory error correction technology ensures accurate and reliable computing results, providing a significant advantage for professional workstation computing and large AI model workloads.
From industrial product design to automotive and aerospace, the new graphics cards unleash the power of exceptional performance and speed to streamline design and manufacturing workflows. They enable professional users to tackle demanding, large-scale photorealistic architectural, engineering, and construction projects in real time while multitasking with ease.
Featuring support for DisplayPort 2.1 technology and powered by the AMD Radiance Display Engine, the new workstation graphics cards deliver stunning visuals with up to 68 billion colours at up to 8K 165 Hz, delivering exceptional colour accuracy and clarity and full coverage of the REC2020 colour space.
Designed for unwavering stability for extended operation, the new workstation graphics cards undergo GIGABYTE’s rigorous high-quality verification and specialized AI computing scenario simulation testing, empowering the graphics cards to excel in both professional workstation and AI applications.
To further enhance work efficiency, GIGABYTE Technology introduces the AI TOP UTILITY exclusive application. Its data-visualized intuitive interface allows users to easily grasp LLM optimization progress and hardware status, and quickly adjust relevant fine-tuning settings, significantly simplifying operation procedures and efficiently driving AI workloads.
