The H800 PCIe 80 GB is a professional graphics card by NVIDIA, launched on March 22nd, 2022. Built on the 4 nm process, and based on the GH100 graphics processor, the card does not support DirectX. Since H800 PCIe 80 GB does not support DirectX 11 or DirectX 12, it might not be able to run all the latest games. The GH100 graphics processor is a large chip with a die area of 814 mm2 and 80,000 million transistors. Unlike the fully unlocked H100 SXM5 80 GB, which uses the same GPU but has all 16896 shaders enabled, NVIDIA has disabled some shading units on the H800 PCIe 80 GB to reach the product’s target shader count. It features 14592 shading units, 456 texture mapping units, and 24 ROPs. Also included are 456 tensor cores which help improve the speed of machine learning applications. NVIDIA has paired 80 GB HBM2e memory with the H800 PCIe 80 GB, which are connected using a 5120-bit memory interface. The GPU is operating at a frequency of 1095 MHz, which can be boosted up to 1755 MHz, memory is running at 1593 MHz.
Being a dual-slot card, the NVIDIA H800 PCIe 80 GB draws power from 1x 16-pin power connector, with power draw rated at 350 W maximum. This device has no display connectivity, as it is not designed to have monitors connected to it. H800 PCIe 80 GB is connected to the rest of the system using a PCI-Express 5.0 x16 interface. The card measures 268 mm in length, 111 mm in width, and features a dual-slot cooling solution.
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NVIDIA H800 80GB Deep Learning GPU Computer Graphics Card
**NVIDIA H800 80GB Deep Learning GPU – Professional AI Powerhouse**
The NVIDIA H800 delivers exceptional deep learning performance with 80GB of high-bandwidth memory, purpose-built for enterprise AI workloads. Featuring advanced Hopper architecture, this professional-grade GPU accelerates training of large language models, computer vision applications, and complex neural networks with unprecedented speed and efficiency.
**Key Features:**
– 80GB ultra-high-capacity memory for massive datasets
– Hopper architecture with enhanced Tensor Cores
– Multi-instance GPU (MIG) technology for workload isolation
– Advanced memory compression and optimization
– Enterprise-grade reliability and support
**Benefits:**
– Dramatically reduces training time for large AI models
– Handles complex datasets without memory constraints
– Maximizes data center efficiency through virtualization
– Scales seamlessly across multi-GPU configurations
– Delivers consistent performance for mission-critical applications
**Unique Selling Points:**
– Industry-leading memory capacity enables training of the largest AI models
– Purpose-engineered for professional deep learning environments
– Optimized for transformer models and generative AI applications
– Enterprise support and certification for production deployments
Ideal for research institutions, AI companies, and enterprises requiring maximum computational power for breakthrough artificial intelligence development.
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| Brand | NVIDIA |
|---|---|
| Products Status | New |
| Application | Workstation |
| ROPs | 24 |
| Interface | PCIe 5.0 x16 |
| Brand | NVIDIA |
|---|---|
| Products Status | New |
| Application | Workstation |
| ROPs | 24 |
| Interface | PCIe 5.0 x16 |
| Memory Size | 80GB |
| Bus Width | 5120bit |
| Cores | 14592 |
| Memory Type | HBM2E |
| Boost Clock | 1755MHz |
| Architecture | Hopper |
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