NVIDIA GH200 Grace Hopper
14,592
CUDA Cores
96GB
VRAM
3000
GB/s
Technical Specifications
14,592
CUDA Cores
1410
Base MHz
1830
Boost MHz
96GB HBM3
5120-bit bus
Performance
67
FP32 TFLOPS
2000
FP16 TFLOPS
1000W
TDP
Cloud Availability
1
Available Instances
$1.99/hr
Starting Price
Detailed Specifications
| Architecture | Hopper (Unknown) |
| Release Date | 2023-05-29 |
| Launch Price | $50,000.00 |
| Process | 4nm |
| Transistors | 80B |
AI Features
Gen 4
Tensor Cores
Enabled
Transformer Engine
Not Supported
Flash Attention
Physical Specifications
Dimensions
12in
Length
5in
Width
3-slot
Height
About GH200 Grace Hopper GPU
The NVIDIA GH200 Grace Hopper is a powerful GPU designed for AI/ML workloads, offering exceptional performance for both training and inference tasks. With 96GB of VRAM and 14,592 CUDA cores, it provides the memory capacity and computational power needed for modern deep learning models.
Released in 2023, the GH200 Grace Hopper features Hopper architecture with advanced AI accelerators including Tensor Cores and Transformer Engine support. This makes it ideal for large language models, computer vision tasks, and generative AI applications.
When considering cloud rental options for the GH200 Grace Hopper, pricing starts at $1.99/hour from various providers. This GPU offers excellent price-to-performance for AI training workloads, with its high memory bandwidth of 3000 GB/s enabling fast data transfer for large datasets.
The GH200 Grace Hopper features CUDA compute capability the latest and is compatible with all major deep learning frameworks including PyTorch, TensorFlow, and JAX. Its 4nm manufacturing process ensures efficient power consumption relative to performance output.
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External Resources
Learn more about GPUs from these authoritative sources:
Official CUDA programming guide
NVIDIA GPU Specifications →Official NVIDIA GPU specs
TechPowerUp GPU Database →Comprehensive GPU specifications
CUDA Compute Capability Guide →GPU compute capability reference
Top GPUs for Training and Inference
| Category | Rank 1 | Rank 2 | Rank 3 |
|---|---|---|---|
| Best for Training | NVIDIA H200 | NVIDIA H100 | NVIDIA B200 |
| Best for Inference | NVIDIA A40 | NVIDIA A100 | NVIDIA A10 |
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