NVIDIA H200
The NVIDIA H200 is a memory-enhanced data center GPU based on the H100, featuring 141GB of HBM3e memory and 4.8 TB/s bandwidth. It delivers significantly higher throughput and lower latency for large language model inference. Available in SXM and NVL form factors, it supports generative AI training and inference, as well as high-performance computing (HPC) workloads.
Core Specifications
CompleteSpecifications
| architecture | Hopper |
| Shape | SXM / NVL Dual-Slot |
| GPU VRAM | 14 1GB HBM3e |
| Memory Bandwidth | 4.8 TB/s |
| FP8 Tensor Core | Up to 3,958 TFLOPS* (SXM sparsity) |
| FP16/BF16 Tensor Core | Up to 1,979 TFLOPS* (SXM sparsity) |
| NVLink | 4th-Gen NVLink, 900 GB/s |
| MIG | Maximum of 7 instances |
| Power Consumption | Up to 700W (SXM) | 600W (NVL) |
| Location | Generative AI Training and Inference, HPC |
* Sparse mode specifications: Dense performance is half that of sparse specs. Specs sourced from NVIDIA's official product page; actual configuration subject to factory settings.
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The NVIDIA H200 is a memory-enhanced data center GPU based on the H100, featuring 141GB of HBM3e memory and 4.8 TB/s bandwidth. It delivers significantly higher throughput and lower latency for large language model inference. Available in SXM and NVL form factors, it supports generative AI training and inference, as well as high-performance computing (HPC) workloads.
| architecture | Hopper |
| Shape | SXM / NVL Dual-Slot |
| GPU VRAM | 14 1GB HBM3e |
| Memory Bandwidth | 4.8 TB/s |
| FP8 Tensor Core | Up to 3,958 TFLOPS* (SXM sparsity) |
| FP16/BF16 Tensor Core | Up to 1,979 TFLOPS* (SXM sparsity) |
| NVLink | 4th-Gen NVLink, 900 GB/s |
| MIG | Maximum of 7 instances |
| Power Consumption | Up to 700W (SXM) | 600W (NVL) |
| Location | Generative AI Training and Inference, HPC |
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