Specifications Compared
| Spec | A30 | H100 |
|---|---|---|
| TDP | 165W | 700W |
| VRAM | 24 GB | 80-94 GB |
| CUDA Cores | 3,584 | 16,896 |
| Memory Type | HBM2 | HBM3 |
| Architecture | Ampere | Hopper |
| Form Factors | PCIe | SXM5, PCIe, NVL |
| Interconnect | NVLink | NVLink, PCIe 5.0, InfiniBand |
| Tensor Cores | 224 | 528 |
| FP16 Performance | 10.3 TFLOPS | 1,979 TFLOPS |
| FP32 Performance | 10.3 TFLOPS | 67 TFLOPS |
| FP64 Performance | 5.2 TFLOPS | 34 TFLOPS |
| INT8 Performance | 165 TOPS | 3,958 TOPS |
| Memory Bandwidth | 933 GB/s | 3,350 GB/s |
Performance Analysis
Compute performance shows stark contrasts between the GPUs. The H100 PCIe offers 1979 TFLOPS FP16 compared to the A30's 10.3 TFLOPS, a roughly 192-fold increase that accelerates deep learning training and inference in half-precision formats common for neural networks. FP32 performance reaches 67 TFLOPS on H100 PCIe versus 10.3 TFLOPS on A30, providing about 6.5 times the throughput for general-purpose floating-point tasks.
Memory specifications heavily favor the H100 PCIe. Its 80 GB HBM3 capacity supports larger batch sizes than the A30's 24 GB HBM2, reducing the need for model sharding in large language models. Bandwidth at 3350 GB/s on H100 PCIe, over 3.6 times the A30's 933 GB/s, minimizes data transfer bottlenecks during training epochs and enables handling of massive datasets without stalling.
FP8 capability on H100 PCIe at 3958 TFLOPS further optimizes inference for quantized models, unavailable on A30. Higher 700W TDP reflects this power but yields superior performance per watt in high-utilization scenarios.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100 PCIe
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Hyperstack | 4×NVIDIA H100 PCIe 80GB VRAM | 80GB | 124 vCPU 720GB RAM 3300GB Storage | Canada | $1.90/GPU/hr $7.60/hr total (4×) | Available | ||
Hyperstack | 2×NVIDIA H100 PCIe 80GB VRAM | 80GB | 60 vCPU 360GB RAM 1600GB Storage | Canada | $1.90/GPU/hr $3.80/hr total (2×) | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.90/GPU/hr $15.20/hr total (8×) | Available | ||
Hyperstack | NVIDIA H100 PCIe 80GB VRAM | 80GB | 28 vCPU 180GB RAM 850GB Storage | Canada | $1.90/GPU/hr | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.95/GPU/hr $15.60/hr total (8×) | Available |
When to Choose the A30
The NVIDIA A30 suits cost-sensitive or power-constrained deployments. With 165W TDP and PCIe form factor, it integrates easily into standard servers without advanced cooling. Workloads fitting within 24 GB HBM2 VRAM, such as smaller-scale inference or legacy Ampere-optimized applications, benefit from its 10.3 TFLOPS FP16/FP32 without overprovisioning resources.
When to Choose the H100 PCIe
NVIDIA H100 PCIe excels in high-throughput AI training and inference. Its 80 GB HBM3 and 3350 GB/s bandwidth handle large models exceeding 24 GB, supporting bigger batches and faster iterations. Deployments needing 1979 TFLOPS FP16 or 3958 TFLOPS FP8, like LLM fine-tuning, justify the 700W TDP and pricing from $1.25 per hour.
Use Cases
H100 PCIe provides 1979 TFLOPS FP16 and 80 GB HBM3, essential for large batch sizes and fast convergence on massive models. A30's 24 GB limits scalability.
3958 TFLOPS FP8 on H100 PCIe optimizes quantized serving for high concurrency. Bandwidth of 3350 GB/s handles peak requests better than A30's 933 GB/s.
67 TFLOPS FP32 and extra VRAM on H100 PCIe accelerate parameter updates on models over 24 GB. A30 suffices only for tiny datasets.
A30's 10.3 TFLOPS FP16 manages standard image generation within 24 GB. H100 PCIe boosts throughput for high-resolution or batched pipelines.
H100 PCIe's 3350 GB/s bandwidth and NVLink support large simulations. A30 works for modest FP32 tasks at 10.3 TFLOPS.
Frequently Asked Questions
What is the VRAM difference between A30 and H100 PCIe?▾
A30 has 24 GB HBM2 VRAM. H100 PCIe offers 80 GB HBM3, allowing three times more model capacity for large AI tasks.
How does H100 PCIe compare to A30 in FP16 performance?▾
H100 PCIe delivers 1979 TFLOPS FP16 versus A30's 10.3 TFLOPS. This gap enables roughly 192 times faster half-precision computations.
What are the power requirements for these GPUs?▾
A30 uses 165W TDP in PCIe form. H100 PCIe requires 700W TDP, demanding robust power and cooling infrastructure.
Is there cloud pricing for H100 PCIe?▾
H100 PCIe starts at $1.25 per hour, averaging $2.79 per hour across 14 live offers. A30 has no current live offers.
Which GPU has higher memory bandwidth?▾
H100 PCIe achieves 3350 GB/s with HBM3. A30 provides 933 GB/s with HBM2, about 3.6 times less.
What architectures do A30 and H100 use?▾
A30 employs Ampere from 2021. H100 uses Hopper from 2022, with features like FP8 support at 3958 TFLOPS.
Which is cheaper to rent, the A30 or the H100?▾
Cloud rental prices for both the A30 and H100 vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.
How much VRAM does the A30 have compared to the H100?▾
The A30 has 24 GB of HBM2 memory. The H100 has 80 to 94 GB of HBM3 memory.
Can I find A30 and H100 GPUs available to rent right now?▾
Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.
What is the main difference between the A30 and the H100?▾
The A30 uses the Ampere architecture (2021) while the H100 uses Hopper (2022). The H100 delivers 192.1x the FP16 throughput and 3.6x the memory bandwidth of the A30.