GPU Model Comparison: H100 vs H200 vs B200 vs A100
Compare Datacenter GPU Specs, Performance & Pricing
Technical specifications for datacenter GPUs including VRAM, memory bandwidth, FP16/FP8 TFLOPS, TDP, and interconnect speeds. Covers NVIDIA Hopper, Blackwell, Ampere, and AMD MI series.
GPU selection impacts training time, model size limits, and infrastructure costs. Understanding the performance/price tradeoffs between H100, H200, B200, and A100 is critical for capacity planning.
Select GPUs to compare side-by-side. Higher TFLOPS = faster training. More VRAM = larger models. Memory bandwidth determines batch throughput. Consider TDP for power planning.
4500 FP8 TFLOPS
$10-15K
192GB
Select GPUs to Compare
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- ✓ Real-world training benchmarks (LLaMA, GPT, Stable Diffusion)
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Side-by-Side Comparison
| Spec | NVIDIA H200 hopper | NVIDIA H100 SXM hopper | NVIDIA A100 80GB ampere |
|---|---|---|---|
| VRAM | 141GB | 80GB | 80GB |
| Memory Type | HBM3e | HBM3 | HBM2e |
| Memory Bandwidth | 4.8 TB/s | 3.35 TB/s | 2 TB/s |
| FP16 TFLOPS | 989 | 989 | 312 |
| FP8 TFLOPS | 1979 | 1979 | N/A |
| TDP | 700W | 700W | 400W |
| Interconnect | NVLink 4 (900 GB/s) | NVLink 4 (900 GB/s) | NVLink 3 (600 GB/s) |
| Typical Price | $35-40K | $30-40K | $10-15K |
| Best For | LLM training, large batch inference | Production AI training | Cost-effective training |
NVIDIA B200
blackwellFrontier training, AGI research
AMD MI300X
amdAMD ecosystem, large VRAM needs
NVIDIA H200
hopperLLM training, large batch inference
NVIDIA H100 SXM
hopperProduction AI training
NVIDIA H100 PCIe
hopperSingle-GPU inference
NVIDIA L40S
ampereInference, rendering
NVIDIA A100 80GB
ampereCost-effective training
NVIDIA A100 40GB
ampereSmall model training
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