CUDA Cores
VRAM
GB/s
3,584
CUDA Cores
930
Base MHz
1440
Boost MHz
24GB HBM2
3072-bit bus
10.3
FP32 TFLOPS
165
FP16 TFLOPS
165W
TDP
0
Available Instances
$0.00/hr
Starting Price
| Architecture | Ampere (Unknown) |
| Release Date | 2021-04-12 |
| Launch Price | $5,000.00 |
| Process | 7nm |
| Transistors | 54.2B |
Gen 3
Tensor Cores
Disabled
Transformer Engine
Not Supported
Flash Attention
10.5in
Length
4.4in
Width
2-slot
Height
The NVIDIA A30 is a powerful GPU designed for AI/ML workloads, offering exceptional performance for both training and inference tasks. With 24GB of VRAM and 3,584 CUDA cores, it provides the memory capacity and computational power needed for modern deep learning models.
Released in 2021, the A30 features Ampere 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 A30, 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 933 GB/s enabling fast data transfer for large datasets.
The A30 features CUDA compute capability 8.0 and is compatible with all major deep learning frameworks including PyTorch, TensorFlow, and JAX. Its 7nm 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.