GPU comparison

A30 vs H100

Specifications and current cloud pricing, side by side.

AmperevsHopperUpdated 34 days ago

The H100 wins for the most common use case of LLM training because its 989 TFLOPS FP16 dense rating and 80 to 94 GB memory exceed the A30 165 TFLOPS and 24 GB limits by wide margins.

A30 listed from $0.35/GPU/hrH100 listed from $2.50/GPU/hr

Right now, from live stock

Specifications Compared

SpecA30H100
TDP165W700W
VRAM24 GB80-94 GB
CUDA Cores3,58416,896
FP8 (dense)Not published1,979 TFLOPS
Memory TypeHBM2HBM3
ArchitectureAmpereHopper
FP16 (dense)165 TFLOPS989 TFLOPS
Form FactorsPCIeSXM5, PCIe, NVL
INT8 (dense)330 TOPS1,979 TOPS
InterconnectNVLink, PCIe 4.0NVLink, PCIe 5.0, InfiniBand
Tensor Cores224528
FP32 Performance10.3 TFLOPS67 TFLOPS
FP64 Performance5.2 TFLOPS34 TFLOPS
Memory Bandwidth933 GB/s3,350 GB/s
FP8 (with sparsity)Not published3,958 TFLOPS
FP16 (with sparsity)330 TFLOPS1,979 TFLOPS
INT8 (with sparsity)661 TOPS3,958 TOPS

Performance Analysis

The FP16 dense performance of the A30 reaches 165 TFLOPS while the H100 reaches 989 TFLOPS dense so the H100 delivers substantially higher throughput for mixed precision workloads. FP32 figures show the A30 at 10.3 TFLOPS against the H100 at 67 TFLOPS which widens the gap for single precision scientific kernels. Memory bandwidth of 933 GB/s on the A30 versus 3350 GB/s on the H100 directly limits sustainable batch sizes on the older card during large model inference. When sparsity is enabled the A30 FP16 figure rises to 330 TFLOPS while the H100 reaches 1979 TFLOPS with sparsity so relative ordering remains unchanged across dense and sparse modes.

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.

A30

A30 is not offered on-demand by any provider we track right now. See the A30 rental page for last-seen listed prices and a price alert.

H100

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
HyperstackCANADA-11$2.50—Deploy
QuantaCloudus-midwest-22$2.59$5.18Deploy
Massed Computeus-central-31$2.73—Deploy
Oridallas-28$2.90$23.20Deploy
Vast.aiCzechia, CZ2$3.22$6.44Deploy

9 providers in stock, 25 offers (cheapest per provider shown). All H100 offers, price history and alerts

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QuantaCloud

Comparing H-series providers? We broker across all of them.

Hopper stock changes by the hour and prices differ by provider. If you need 16+ GPUs reserved or a cluster in the next 90 days, we quote H-series or B300 inventory at partner rates: one quote, 24h turnaround.

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When to Choose the A30

The A30 suits deployments where 24 GB HBM2 memory meets workload demands and power draw must stay at 165 W TDP. PCIe only form factor and PCIe 4.0 interconnect further align the A30 with existing server infrastructures that lack SXM5 or InfiniBand support.

When to Choose the H100

The H100 fits workloads that require 80 to 94 GB HBM3 capacity together with 3350 GB/s bandwidth for large batch training. FP16 dense throughput of 989 TFLOPS and FP32 throughput of 67 TFLOPS accelerate both training and inference relative to the A30 while NVLink and PCIe 5.0 options enable tighter multi GPU scaling.

Use Cases

LLM Training
H100

The H100 supplies 989 TFLOPS FP16 dense and 80 to 94 GB memory which exceed the A30 165 TFLOPS and 24 GB limits.

LLM Inference
H100

The H100 provides 3350 GB/s bandwidth and 1979 TFLOPS FP16 with sparsity enabling larger batches than the A30 933 GB/s and 330 TFLOPS with sparsity.

Fine-tuning
H100

FP32 performance of 67 TFLOPS on the H100 surpasses the A30 10.3 TFLOPS while 80 to 94 GB memory accommodates adapter layers.

Stable Diffusion
Either

The A30 24 GB memory suffices for many diffusion resolutions at 165 W TDP yet the H100 3350 GB/s bandwidth accelerates higher resolution generation.

Scientific Computing
H100

The H100 FP32 rating of 67 TFLOPS and 3350 GB/s bandwidth outperform the A30 10.3 TFLOPS and 933 GB/s for simulation workloads.

Frequently Asked Questions

What are the FP16 dense ratings?▾

The A30 lists 165 TFLOPS FP16 dense and the H100 lists 989 TFLOPS FP16 dense.

Which GPU offers higher memory bandwidth?▾

The H100 reaches 3350 GB/s while the A30 reaches 933 GB/s.

What power limits apply to each card?▾

The A30 TDP is 165 W and the H100 TDP is 700 W.

Do both GPUs support NVLink?▾

Both the A30 and H100 include NVLink interconnect support.

What FP32 performance is published?▾

The A30 publishes 10.3 TFLOPS FP32 and the H100 publishes 67 TFLOPS FP32.

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 6.0x the dense FP16 throughput (989 vs 165 TFLOPS, both without sparsity) and 3.6x the memory bandwidth of the A30.

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 A30 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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