H100 PCIe vs Tesla V100 32GB

HoppervsVoltaUpdated 35 days ago

The H100 PCIe emerges as the clear winner for prevalent AI and machine learning tasks: its 1979 TFLOPS FP16 and 80 GB VRAM enable handling of modern large language models infeasible on V100's 125 TFLOPS and 32 GB limits. Despite higher $2.68 per hour average pricing, superior performance yields faster ROI through reduced training times.

H100 PCIe from $1.90/hrTesla V100 32GB from $0.19/hr

Specifications Compared

SpecH100V100
TDP700W300W
VRAM80-94 GB16-32 GB
CUDA Cores16,8965,120
Memory TypeHBM3HBM2
ArchitectureHopperVolta
Form FactorsSXM5, PCIe, NVLSXM2, PCIe
InterconnectNVLink, PCIe 5.0, InfiniBandNVLink, PCIe 3.0
Tensor Cores528640
FP8 Performance3,958 TFLOPS
FP16 Performance1,979 TFLOPS125 TFLOPS
FP32 Performance67 TFLOPS15.7 TFLOPS
FP64 Performance34 TFLOPS7.8 TFLOPS
INT8 Performance3,958 TOPS
Memory Bandwidth3,350 GB/s900 GB/s

Performance Analysis

The H100 PCIe dominates in raw compute power: its 1979 TFLOPS FP16 rating dwarfs the V100 32GB's 125 TFLOPS, accelerating deep learning training where half-precision dominates. FP32 performance follows suit at 67 TFLOPS versus 15.7 TFLOPS, benefiting simulations and general-purpose computing. These deltas translate to 15x faster training iterations on large neural networks, reducing epoch times from days to hours.

Memory specs reshape workload feasibility: H100's 80 GB HBM3 versus V100's 32 GB HBM2 supports batch sizes up to 2.5x larger, minimizing out-of-memory errors in transformer models. The 3350 GB/s bandwidth, over 3.7x the V100's 900 GB/s, sustains high utilization during data-intensive phases like gradient accumulation. Inference benefits from H100's FP8 at 3958 TFLOPS, enabling low-latency serving of billion-parameter LLMs.

Power draw underscores trade-offs: H100's 700W TDP demands robust cooling versus V100's efficient 300W, impacting datacenter density. Overall, H100 excels in memory-bound and compute-heavy scenarios, while V100 suffices for smaller-scale operations.

Live Cloud Pricing

Real-time prices from 25+ providers. Updated every 60 seconds.

H100 PCIe

ProviderGPU ModelVRAMHost SpecsRegionPriceStatusAction
Hyperstack
Hyperstack
4×NVIDIA H100 PCIe
80GB VRAM
$1.90/GPU/hr
$7.60/hr total (4×)
Available
Hyperstack
Hyperstack
2×NVIDIA H100 PCIe
80GB VRAM
$1.90/GPU/hr
$3.80/hr total (2×)
Available
Hyperstack
Hyperstack
8×NVIDIA H100 PCIe
80GB VRAM
$1.90/GPU/hr
$15.20/hr total (8×)
Available
Hyperstack
Hyperstack
NVIDIA H100 PCIe
80GB VRAM
$1.90/GPU/hr
Available
Hyperstack
Hyperstack
8×NVIDIA H100 PCIe
80GB VRAM
$1.95/GPU/hr
$15.60/hr total (8×)
Available

Tesla V100 32GB

ProviderGPU ModelVRAMHost SpecsRegionPriceStatusAction
TensorDock
TensorDock
NVIDIA Tesla V100 16GB
16GB VRAM
$0.19/GPU/hr
Available
TensorDock
TensorDock
NVIDIA Tesla V100 16GB
16GB VRAM
$0.19/GPU/hr
Available
TensorDock
TensorDock
NVIDIA Tesla V100 32GB
32GB VRAM
$0.29/GPU/hr
Available
TensorDock
TensorDock
NVIDIA Tesla V100 32GB
32GB VRAM
$0.29/GPU/hr
Available
Lambda Labs
Lambda Labs
8×NVIDIA Tesla V100 16GB
16GB VRAM
$0.79/GPU/hr
$6.32/hr total (8×)
Available

Compare real-time pricing across 25+ providers

When to Choose the H100 PCIe

Select the H100 PCIe for large-scale AI training and inference: its 80 GB VRAM handles models exceeding 32 GB, such as 70B-parameter LLMs, without multi-GPU sharding. The 1979 TFLOPS FP16 and 3958 TFLOPS FP8 deliver rapid convergence and high-throughput serving, ideal for production environments.

Enterprises with NVLink or PCIe 5.0 infrastructure benefit from H100's interconnects, enabling efficient multi-node scaling at $1.25 per hour starting price.

When to Choose the Tesla V100 32GB

Opt for the V100 32GB in budget-constrained or legacy setups: at $0.29 per hour average $1.01, it undercuts H100 costs by over 60 percent while delivering 125 TFLOPS FP16 for prototyping.

It suits PCIe 3.0 clusters running established Volta-optimized code, where 32 GB VRAM and 300W TDP fit dense, low-power deployments without refactoring.

Use Cases

LLM Training
H100 PCIe

H100's 1979 TFLOPS FP16 outperforms V100's 125 TFLOPS by over 15x, slashing training times for billion-parameter models. Its 80 GB VRAM supports massive batches without splitting.

LLM Inference
H100 PCIe

H100's 3958 TFLOPS FP8 enables low-latency serving of large models, far beyond V100's capabilities. The 3350 GB/s bandwidth handles high request volumes efficiently.

Fine-tuning
H100 PCIe

With 67 TFLOPS FP32 and 80 GB VRAM, H100 accelerates fine-tuning on datasets too large for V100's 15.7 TFLOPS and 32 GB. It reduces iterations significantly.

Stable Diffusion
H100 PCIe

H100's superior FP16 and memory bandwidth generate images 10x faster than V100, supporting high-resolution diffusion models. Larger VRAM fits complex pipelines.

Scientific Computing
Either

V100's 15.7 TFLOPS FP32 suffices for many simulations at low $0.29 per hour cost. H100's 67 TFLOPS excels in memory-intensive HPC but at higher power and price.

Frequently Asked Questions

What is the VRAM difference between H100 PCIe and V100 32GB?

H100 PCIe provides 80 GB HBM3 VRAM, doubling the V100 32GB's 32 GB HBM2 capacity. This allows H100 to process larger models and batches without errors. Bandwidth reaches 3350 GB/s on H100 versus 900 GB/s on V100.

How do FP16 performance figures compare?

H100 PCIe delivers 1979 TFLOPS FP16, approximately 15.8 times the V100 32GB's 125 TFLOPS. This gap accelerates AI training significantly. FP32 follows at 67 TFLOPS for H100 against 15.7 TFLOPS.

What are the current cloud rental prices?

H100 PCIe rents from $1.25 per hour, averaging $2.68 per hour across 16 offers. V100 32GB starts at $0.29 per hour, averaging $1.01 per hour over 46 offers. Prices reflect performance disparities.

Which has higher power consumption?

H100 PCIe draws 700W TDP, more than double the V100 32GB's 300W. This impacts cooling and density in deployments. H100 justifies it with superior compute.

Can V100 run modern LLMs?

V100 32GB handles smaller LLMs up to 7B parameters with 32 GB VRAM, but struggles with larger ones due to limited 125 TFLOPS FP16. H100's 80 GB supports 70B models seamlessly.

What interconnects do they support?

H100 PCIe uses PCIe 5.0 and NVLink, outperforming V100's PCIe 3.0 and NVLink. This enables faster multi-GPU communication. InfiniBand pairs with both for clusters.

Which is cheaper to rent, the H100 or the V100?

Cloud rental prices for both the H100 and V100 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 H100 have compared to the V100?

The H100 has 80 to 94 GB of HBM3 memory. The V100 has 16 to 32 GB of HBM2 memory.

Can I find H100 and V100 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 H100 and the V100?

The H100 uses the Hopper architecture (2022) while the V100 uses Volta (2017). The H100 delivers 15.8x the FP16 throughput and 3.7x the memory bandwidth of the V100.

H100 PCIe vs Tesla V100 32GB: 94GB vs 32GB | GPUPerHour