Specifications Compared
| Spec | H100 | V100 |
|---|---|---|
| TDP | 700W | 300W |
| VRAM | 80-94 GB | 16-32 GB |
| CUDA Cores | 16,896 | 5,120 |
| Memory Type | HBM3 | HBM2 |
| Architecture | Hopper | Volta |
| Form Factors | SXM5, PCIe, NVL | SXM2, PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | NVLink, PCIe 3.0 |
| Tensor Cores | 528 | 640 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 125 TFLOPS |
| FP32 Performance | 67 TFLOPS | 15.7 TFLOPS |
| FP64 Performance | 34 TFLOPS | 7.8 TFLOPS |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 3,350 GB/s | 900 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
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 QuantaCloud Partner | H100 PCIe 32–1024+ GPUs · InfiniBand | ∞ | Custom configs | Multiple DCs | Reserved / cluster Get a quote in 24h | Available | ||
 Nebius | NVIDIA H100 SXM5 80GB VRAM | 80GB | 16 vCPU 200GB RAM | 🌍Europe | $2.15/GPU/hr | |||
 Vast.ai | NVIDIA H100 SXM5 80GB VRAM | 80GB | 128 vCPU 126GB RAM 1457GB Storage | Netherlands | $2.20/GPU/hr | Available | ||
 Denvr | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 1024GB RAM 22800GB Storage | Virginia | $2.30/GPU/hr $18.40/hr total (8×) | |||
 CoreWeave | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 128 vCPU 0GB RAM 61440GB Storage | United States | $2.44/GPU/hr $19.51/hr total (8×) | |||
 Cirrascale | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 192 vCPU 2048GB RAM 39738GB Storage | United States | $2.49/GPU/hr $19.92/hr total (8×) |
Tesla V100 32GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Lambda Labs | 8×NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 88 vCPU 448GB RAM 6041GB Storage | Texas | $0.79/GPU/hr $6.32/hr total (8×) | Available | ||
 Ori | 4×NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 32 vCPU 180GB RAM 400GB Storage | Lille | $0.83/GPU/hr $3.32/hr total (4×) | Available | ||
Ori | 4×NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 36 vCPU 180GB RAM 4050GB Storage | Lille | $0.83/GPU/hr $3.32/hr total (4×) | Available | ||
Ori | 2×NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 16 vCPU 90GB RAM 400GB Storage | Beauharnois | $0.83/GPU/hr $1.66/hr total (2×) | Available | ||
Ori | 2×NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 16 vCPU 90GB RAM 400GB Storage | Lille | $0.83/GPU/hr $1.66/hr total (2×) | Available |
QuantaCloud
Comparing H-series providers? We broker across all of them.
Most Hopper capacity is sold out through Q3 2026. If you need 16+ GPUs reserved or a cluster in the next 90 days, we quote remaining H-series or B300 inventory at partner rates — one quote, 24h turnaround.
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
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.
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.
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.
H100's superior FP16 and memory bandwidth generate images 10x faster than V100, supporting high-resolution diffusion models. Larger VRAM fits complex pipelines.
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.