Specifications Compared
| Spec | A100 | GH200 |
|---|---|---|
| TDP | 400W | 900W |
| VRAM | 40-80 GB | 96 GB |
| CUDA Cores | 6,912 | 16,896 |
| Memory Type | HBM2e | HBM3 |
| Architecture | Ampere | Hopper |
| Form Factors | SXM4, PCIe | SXM |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | NVLink-C2C, PCIe 5.0 |
| Tensor Cores | 432 | 528 |
| FP16 Performance | 312 TFLOPS | 1,979 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 67 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | 34 TFLOPS |
| INT8 Performance | 624 TOPS | 3,958 TOPS |
| Memory Bandwidth | 2,039 GB/s | 4,000 GB/s |
Performance Analysis
The GH200 outperforms the A100 dramatically in compute capabilities: its 1979 TFLOPS FP16 enables faster AI model training than the A100's 312 TFLOPS, reducing epochs for large language models. FP32 performance of 67 TFLOPS on the GH200 supports 3.4 times the throughput of the A100's 19.5 TFLOPS, benefiting scientific simulations and precision tasks. The addition of 3958 TFLOPS FP8 on the GH200 accelerates inference for quantized models. Memory differences prove critical: 96 GB HBM3 versus 80 GB HBM2e allows larger batch sizes, and 4000 GB/s bandwidth doubles the A100's 2039 GB/s to minimize data bottlenecks in training. Higher TDP of 900W on the GH200 versus 400W demands robust cooling, but NVLink-C2C interconnect enhances multi-GPU scaling over the A100's NVLink.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 SXM4 80GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 63GB RAM 2826GB Storage | Slovenia | $0.73/GPU/hr | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 794GB Storage | Slovenia | $0.73/GPU/hr $1.47/hr total (2×) | Available | ||
 LeaderGPU | 8×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.90/GPU/hr $7.20/hr total (8×) | Available | ||
Vast.ai | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 63GB RAM 646GB Storage | Czechia | $1.07/GPU/hr | Available | ||
 Denvr | 8×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 128 vCPU 1024GB RAM 15200GB Storage | Virginia | $1.15/GPU/hr $9.20/hr total (8×) |
GH200 Grace Hopper
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | Atlanta | $1.99/GPU/hr | Available | ||
 Lambda Labs | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 64 vCPU 432GB RAM 4096GB Storage | Virginia | $2.29/GPU/hr | Available | ||
Denvr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 7600GB Storage | Virginia | $3.87/GPU/hr | |||
 CoreWeave | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 7680GB Storage | United States | $6.50/GPU/hr |
When to Choose the A100 SXM4 80GB
The A100 SXM4 80GB suits cost-conscious deployments where maturity matters. With pricing from $0.67 per hour and availability across 22 cloud offers, it delivers reliable 312 TFLOPS FP16 for standard AI training without the GH200's premium. Lower 400W TDP fits power-limited environments, and PCIe 4.0 compatibility eases integration in legacy clusters.
When to Choose the GH200 Grace Hopper
The GH200 Grace Hopper excels in high-performance scenarios demanding peak throughput. Its 1979 TFLOPS FP16 and 96 GB HBM3 handle massive models infeasible on the A100, while 4000 GB/s bandwidth supports enormous batch sizes. PCIe 5.0 and NVLink-C2C enable future-proof scaling despite higher $1.99 per hour starting price.
Use Cases
GH200's 1979 TFLOPS FP16 and 96 GB HBM3 enable training larger models faster than A100's 312 TFLOPS and 80 GB. Bandwidth of 4000 GB/s supports bigger batches.
3958 TFLOPS FP8 on GH200 accelerates quantized inference beyond A100 capabilities. Higher FP16 sustains real-time serving at scale.
A100's 19.5 TFLOPS FP32 suffices for many fine-tuning tasks at lower $1.43 per hour average. GH200's 67 TFLOPS FP32 speeds up complex adaptations.
A100's 312 TFLOPS FP16 handles image generation efficiently at $0.67 per hour starting price. Proven ecosystem reduces setup time.
GH200's 67 TFLOPS FP32 outperforms A100's 19.5 TFLOPS for simulations. NVLink-C2C aids multi-node precision work.
Frequently Asked Questions
What is the VRAM difference between A100 SXM4 80GB and GH200?▾
The A100 offers 80 GB HBM2e, while GH200 provides 96 GB HBM3. This extra capacity on GH200 supports larger models without swapping.
How does memory bandwidth compare?▾
GH200 achieves 4000 GB/s, nearly double the A100's 2039 GB/s. Higher bandwidth reduces training bottlenecks for data-intensive tasks.
Which has better FP16 performance?▾
GH200 delivers 1979 TFLOPS FP16 versus A100's 312 TFLOPS. This gap accelerates deep learning training significantly.
What are the cloud pricing differences?▾
A100 SXM4 80GB starts at $0.67 per hour averaging $1.43 across 22 offers. GH200 begins at $1.99 per hour averaging $3.33 over 5 offers.
Is GH200 more power-hungry?▾
Yes, GH200's 900W TDP exceeds A100's 400W. It requires advanced cooling for sustained high performance.
Which architecture is newer?▾
GH200 uses Hopper from 2023, succeeding A100's Ampere from 2020. Hopper includes FP8 support at 3958 TFLOPS.
Which is cheaper to rent, the A100 or the GH200?▾
Cloud rental prices for both the A100 and GH200 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 A100 have compared to the GH200?▾
The A100 has 40 to 80 GB of HBM2e memory. The GH200 has 96 GB of HBM3 memory.
Can I find A100 and GH200 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 A100 and the GH200?▾
The A100 uses the Ampere architecture (2020) while the GH200 uses Hopper (2023). The GH200 delivers 6.3x the FP16 throughput and 2.0x the memory bandwidth of the A100.