CUDA Cores
VRAM
GB/s
14,592
CUDA Cores
1410
Base MHz
1830
Boost MHz
138GB HBM3
5120-bit bus
67
FP32 TFLOPS
2000
FP16 TFLOPS
700W
TDP
8
Available Instances
$1.47/hr
Starting Price
| Architecture | Hopper (Unknown) |
| Release Date | 2022-09-20 |
| Launch Price | $30,000.00 |
| Process | 4nm |
| Transistors | 80B |
Gen 4
Tensor Cores
Enabled
Transformer Engine
Supported
Flash Attention
10.5in
Length
4.4in
Width
2-slot
Height
The NVIDIA H100 is a powerful GPU designed for AI/ML workloads, offering exceptional performance for both training and inference tasks. With 138GB of VRAM and 14,592 CUDA cores, it provides the memory capacity and computational power needed for modern deep learning models.
Released in 2022, the H100 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 H100, pricing starts at $1.47/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 H100 supports the latest CUDA compute capabilities 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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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
| 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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