A30 GPU
The NVIDIA A30 is a versatile data center GPU for mainstream AI inference, training, and HPC workloads with Multi-Instance GPU support.

Cloud Pricing
Cheapest on Seeweb — 48% below avgPrices updated daily. Last check: 4/8/2026
Performance
Strengths & Limitations
- 24GB HBM2 memory capacity supports large model inference and training
- Multi-Instance GPU (MIG) enables partitioning into up to 4 isolated instances
- 165W TDP allows for dense server configurations
- Third-generation Tensor Cores provide optimized mixed-precision AI performance
- Third-generation NVLink connectivity at 200 GB/s for multi-GPU scaling
- 933 GB/s memory bandwidth supports memory-intensive workloads
- PCIe Gen4 interface provides improved host connectivity over previous generations
- 165W power consumption may be high for edge deployment scenarios
- Limited to Ampere architecture features, lacking newer Hopper or Blackwell capabilities
- 10.3 TFLOPS FP32 performance may be insufficient for large-scale HPC workloads
- Released in 2021, representing previous-generation technology compared to current offerings
- Dual-slot form factor reduces server density compared to single-slot alternatives
Key Features
About A30
Common Use Cases
The A30 is well-suited for AI inference serving that requires substantial memory capacity, medium-scale AI training workloads, and HPC applications that can leverage GPU acceleration. Its 24GB memory makes it capable of handling large language models and computer vision tasks that exceed the memory limits of smaller GPUs. The MIG functionality makes it particularly valuable in multi-tenant cloud environments where GPU resources need to be shared among multiple users or applications while maintaining isolation. Data analytics workloads involving large datasets benefit from the combination of memory capacity and compute performance.
Full Specifications
Hardware
- Manufacturer
- NVIDIA
- Architecture
- Ampere
- CUDA Cores
- 3,584
- Tensor Cores
- 224
- TDP
- 165W
Memory & Performance
- VRAM
- 24GB
- Memory Bandwidth
- 933 GB/s
- FP32
- 10.3 TFLOPS
- FP16
- 165 TFLOPS
- FP64
- 5.2 TFLOPS
- Release
- 2021
Frequently Asked Questions
How much does an A30 cost per hour in the cloud?
A30 pricing varies by provider, region, and commitment level. Check the pricing table above for current rates across all providers.
What is the A30 best used for?
The A30 excels at AI inference workloads requiring substantial memory, medium-scale AI training, and HPC applications. Its 24GB memory capacity and MIG support make it particularly suitable for serving large models and multi-tenant deployments where resource isolation is important.
How does the A30 compare to the V100 for AI workloads?
The A30 offers up to 3x higher throughput than the V100 for AI training and inference tasks, primarily due to its third-generation Tensor Cores and Ampere architecture optimizations. The A30 also provides MIG functionality and 24GB of memory compared to the V100's 16GB or 32GB options, though the V100 offers higher memory bandwidth in its HBM2 configuration.