OCG7870-10H4-R

Product Highlights (Bare Chassis Only – No System Components Included)

• Massive GPU Capacity – Supports up to 10 NVIDIA RTX 4090 GPUs, delivering extreme parallel processing power for AI, deep learning, scientific computing, and rendering tasks.

• Versatile Motherboard Compatibility – Compatible with EEB, CEB, ATX, and Micro ATX form factors, including AsrockROME2D32GM-2T and AsrockGENOA2D24G-2L-R101 server boards.

• Optimized Cooling System – Equipped with 8 × 8038 center fans and 3 × 12038 rear fans for exceptional airflow; optional configuration with 8 × 8056 center fans and 5 × 8038 rear fans for enhanced thermal management.

• High-Density Storage Support – The front panel accommodates 4 × 2.5-inch SAS/SATA direct-plug or hot-plug hard drives for flexible storage expansion.

• Redundant Power Supply Options – Supports CRPS redundant PSU configurations (4+1, 3+2, 2+2, 3+1) for maximum uptime and reliability.

• Flexible PCIe Gen5 Riser Options – Choose between PCI-E-16X Gen5 Riser Cable or PCI-E-16X Gen5 Riser with MCIO Cable for optimal GPU connectivity.

• Durable Industrial-Grade Build – Made with Baosteel SGCC 1.0–1.2mm steel for strength and long-lasting performance.

• Tool-Free Access & Maintenance – Easy-to-use front panel with USB 3.0 ports, power/reset switches, and indicator lights for power, storage, and network status.

Application Fields

• Artificial Intelligence & Deep Learning – Ideal for training and inference workloads requiring high GPU parallelism.

• High-Performance Computing (HPC) – Perfect for scientific simulations, engineering analysis, and large-scale data processing.

• 3D Rendering & Video Production – Supports professional rendering farms and high-end content creation workflows.

• Cloud Gaming & Virtualization – Capable of hosting multiple virtualized GPU instances for cloud-based gaming platforms.

• Blockchain & Cryptocurrency Mining – Configurable for large-scale GPU mining farms.

• Big Data Analytics – Suitable for real-time data analysis and large-scale data modeling.

• Research & Academic Labs – Used in universities and research centers for computational research and AI experiments.