CUDA Cores
VRAM
GB/s
3,584
CUDA Cores
1190
Base MHz
1328
Boost MHz
16GB HBM2
4096-bit bus
9.3
FP32 TFLOPS
18.7
FP16 TFLOPS
250W
TDP
0
Available Instances
$0.00/hr
Starting Price
| Architecture | Pascal (Unknown) |
| Release Date | 2016-06-20 |
| Launch Price | $10,000.00 |
| Process | 16nm |
| Transistors | 15.3B |
none
Tensor Cores
Disabled
Transformer Engine
Not Supported
Flash Attention
10.5in
Length
4.4in
Width
2-slot
Height
The NVIDIA Tesla P100 is a powerful GPU designed for AI/ML workloads, offering exceptional performance for both training and inference tasks. With 16GB of VRAM and 3,584 CUDA cores, it provides the memory capacity and computational power needed for modern deep learning models.
Released in 2016, the Tesla P100 features Pascal 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 P100, pricing starts at $0.00/hour from various providers. This GPU offers excellent price-to-performance for AI training workloads, with its high memory bandwidth of 732 GB/s enabling fast data transfer for large datasets.
The Tesla P100 features CUDA compute capability the latest and is compatible with all major deep learning frameworks including PyTorch, TensorFlow, and JAX. Its 16nm manufacturing process ensures efficient power consumption relative to performance output.
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 |
Compare GPU specifications and cloud instances to find the best GPU for your workload.