GPU comparison

A100 vs H100

Specifications and current cloud pricing, side by side.

AmperevsHopperUpdated 41 days ago

The H100 wins for the most common use case of LLM training because its FP16 dense performance of 989 TFLOPS exceeds the A100 figure of 312 TFLOPS while its memory bandwidth of 3350 GB/s exceeds 2039 GB/s.

A100 from $0.68/GPU/hrH100 from $2.50/GPU/hr

Right now, from live stock

  • Cheapest right now: A100 at $0.68/hr on LeaderGPU

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  • Most providers in stock: H100 (12)

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  • Best $ per TFLOPS FP16 dense right now: A100 ($0.0022 per TFLOPS-hour at 312 TFLOPS)

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Specifications Compared

SpecA100H100
TDP400W700W
VRAM40-80 GB80-94 GB
CUDA Cores6,91216,896
FP8 (dense)Not published1,979 TFLOPS
Memory TypeHBM2eHBM3
ArchitectureAmpereHopper
FP16 (dense)312 TFLOPS989 TFLOPS
Form FactorsSXM4, PCIeSXM5, PCIe, NVL
INT8 (dense)624 TOPS1,979 TOPS
InterconnectNVLink, PCIe 4.0, InfiniBandNVLink, PCIe 5.0, InfiniBand
Tensor Cores432528
FP32 Performance19.5 TFLOPS67 TFLOPS
FP64 Performance9.7 TFLOPS34 TFLOPS
Memory Bandwidth2,039 GB/s3,350 GB/s
FP8 (with sparsity)Not published3,958 TFLOPS
FP16 (with sparsity)624 TFLOPS1,979 TFLOPS
INT8 (with sparsity)1,248 TOPS3,958 TOPS

Performance Analysis

FP16 dense performance reaches 312 TFLOPS on the A100 and 989 TFLOPS on the H100. The FP16 dense to FP32 ratio equals 312 divided by 19.5 on the A100 and 989 divided by 67 on the H100. This ratio indicates acceleration potential for mixed precision workloads in training and inference. Memory bandwidth of 3350 GB/s on the H100 compared with 2039 GB/s on the A100 supports larger batch sizes during model execution. FP16 with sparsity reaches 624 TFLOPS on the A100 and 1979 TFLOPS on the H100 so sparsity comparisons must stay separate from dense figures.

Current On-Demand Offers

Cheapest secure on-demand offer per provider that is reported in stock right now, per GPU per hour; multi-GPU instances show the whole-instance price alongside. Deploy opens the DeployGPU console for providers on the platform, otherwise the provider's own site. Stock is rechecked every minute.

A100

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
LeaderGPUThe Netherlands8$0.68$5.42Deploy
Vast.aiCzechia, CZ1$1.05—Deploy
ThunderComputeUSA1$1.09—Deploy
Massed Computeus-central-34$1.35$5.40Deploy
HyperstackCANADA-14$1.35$5.40Deploy

9 providers in stock, 33 offers (cheapest per provider shown). All A100 offers, price history and alerts

H100

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
HyperstackCANADA-14$2.50$10.00Deploy
QuantaCloudus-midwest-21$2.59—Deploy
Massed Computeus-central-31$2.73—Deploy
RunPodglobal1$2.89—Deploy
Oridallas-22$2.90$5.80Deploy

12 providers in stock, 24 offers (cheapest per provider shown). All H100 offers, price history and alerts

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When to Choose the A100

The A100 suits environments that prioritize a TDP of 400W over higher throughput. Workloads that rely on INT8 dense performance of 624 TOPS without sparsity activation also favor the A100. Its 40 to 80 GB HBM2e configuration fits deployments where memory capacity beyond 80 GB is unnecessary.

When to Choose the H100

The H100 fits workloads that require FP16 dense performance of 989 TFLOPS or FP8 dense performance of 1979 TFLOPS. Its memory bandwidth of 3350 GB/s enables larger batch processing than the 2039 GB/s available on the A100. The 80 to 94 GB HBM3 capacity supports models that exceed 80 GB memory needs.

Use Cases

LLM Training
H100

The H100 delivers FP16 dense performance of 989 TFLOPS against 312 TFLOPS on the A100.

LLM Inference
H100

The H100 provides FP8 dense performance of 1979 TFLOPS while the A100 does not publish an FP8 figure.

Fine-tuning
H100

The H100 memory bandwidth of 3350 GB/s exceeds the A100 bandwidth of 2039 GB/s for efficient parameter updates.

Stable Diffusion
Either

Both GPUs support INT8 dense performance though the H100 reaches 1979 TOPS and the A100 reaches 624 TOPS.

Scientific Computing
A100

The A100 TDP of 400W is lower than the H100 TDP of 700W for sustained power constrained runs.

Frequently Asked Questions

What is the memory bandwidth difference between A100 and H100?▾

The A100 lists memory bandwidth of 2039 GB/s. The H100 lists memory bandwidth of 3350 GB/s.

How does FP16 dense performance compare on A100 versus H100?▾

The A100 achieves 312 TFLOPS in FP16 dense. The H100 achieves 989 TFLOPS in FP16 dense.

What TDP values apply to the A100 and H100?▾

The A100 has a TDP of 400W. The H100 has a TDP of 700W.

Which GPU offers higher FP32 performance?▾

The A100 reaches 19.5 TFLOPS in FP32. The H100 reaches 67 TFLOPS in FP32.

Do the GPUs support the same interconnect options?▾

Both support NVLink and InfiniBand. The H100 adds PCIe 5.0 while the A100 uses PCIe 4.0.

Which is cheaper to rent, the A100 or the H100?▾

Cloud rental prices for both the A100 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 A100 have compared to the H100?▾

The A100 has 40 to 80 GB of HBM2e memory. The H100 has 80 to 94 GB of HBM3 memory.

Can I find A100 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 A100 and the H100?▾

The A100 uses the Ampere architecture (2020) while the H100 uses Hopper (2022). The H100 delivers 3.2x the dense FP16 throughput (989 vs 312 TFLOPS, both without sparsity) and 1.6x the memory bandwidth of the A100.

Rent these GPUs

Each GPU page lists every current on-demand offer by provider, per GPU-hour, updated every minute.

Related comparisons

How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the A100 and the H100. Dense and sparse throughput are listed separately.
  • Prices and availability are live: every offer shown is an in-stock, on-demand listing from a provider we track, rechecked every minute.
  • The written comparison (overview, performance notes, when to choose each card, verdict, use cases and FAQ) was drafted with an AI model from the specification table above and passed an automated check that rejects any figure not in that table. It was last generated on . It contains no prices; those are always read live.
  • Read how we collect the data, or report an error on this page.

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