Accelerate your professional workflows with the ASRock Intel Arc Pro B70 Creator 32GB Workstation Graphics Card. Built on the Intel Xe2-HPG architecture, this card features 32 Xe cores and 256 XMX engines, designed to accelerate AI, rendering, and complex visualization workloads . With 32GB of high-speed GDDR6 memory on a 256-bit bus running at 19 Gbps, it allows for handling large AI models and complex datasets locally . The advanced blower-style cooling system with a high-efficiency vapor chamber and Honeywell PTM7950 phase-change material ensures sustained performance under heavy professional loads .
Key Features
Professional Intel Arc Pro B70 GPU: Built on the Intel Xe2-HPG architecture, it features 32 Xe cores and 256 XMX engines, designed to accelerate AI, rendering, and complex visualization workloads .
Massive 32GB GDDR6 VRAM: Equipped with 32GB of high-speed GDDR6 memory on a 256-bit bus, running at 19 Gbps, which allows for handling large AI models and complex datasets locally .
High-Performance Engine Clock: Delivers an engine clock of 2540 MHz, providing the compute power needed for demanding professional applications and AI inference .
Next-Gen PCIe 5.0 Interface: Utilizes a PCI Express 5.0 x16 interface, ensuring maximum data transfer bandwidth for seamless interaction with the latest workstation platforms .
Advanced Cooling for Sustained Performance: Features a robust blower-style cooling system combined with a high-efficiency vapor chamber and Honeywell PTM7950 phase-change material for excellent thermal conductivity and sustained performance .
Quad DisplayPort 2.1 Outputs: Includes four DisplayPort 2.1 ports, supporting multi-display setups with the latest high-resolution, high-refresh-rate professional monitors .
Professional-Grade Construction: Built with a die-cast metal shroud, a metal backplate, and ASRock's Super Alloy Graphics Card components, ensuring durability and reliability in demanding environments .
Optimized for Multi-GPU & Linux Workloads: Supports scalable multi-GPU configurations under Linux, making it ideal for large language model (LLM) deployments and other intensive compute tasks .
