CUDA Cores
VRAM
GB/s
5,120
CUDA Cores
1245
Base MHz
1455
Boost MHz
32GB HBM2
4096-bit bus
14
FP32 TFLOPS
112
FP16 TFLOPS
300W
TDP
2
Available Instances
$0.18/hr
Starting Price
| Architecture | Volta (Unknown) |
| Release Date | 2017-06-20 |
| Launch Price | $10,000.00 |
| Process | 12nm |
| Transistors | 21.1B |
Gen 1
Tensor Cores
Disabled
Transformer Engine
Not Supported
Flash Attention
10.5in
Length
4.4in
Width
2-slot
Height
The NVIDIA Tesla V100 is a powerful GPU designed for AI/ML workloads, offering exceptional performance for both training and inference tasks. With 32GB of VRAM and 5,120 CUDA cores, it provides the memory capacity and computational power needed for modern deep learning models.
Released in 2017, the Tesla V100 features Volta 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 Tesla V100, pricing starts at $0.18/hour from various providers. This GPU offers excellent price-to-performance for AI training workloads, with its high memory bandwidth of 900 GB/s enabling fast data transfer for large datasets.
The Tesla V100 features CUDA compute capability the latest and is compatible with all major deep learning frameworks including PyTorch, TensorFlow, and JAX. Its 12nm 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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