Specifications Compared
| Spec | H100 | QUADRO-RTX-6000 |
|---|---|---|
| TDP | 700W | 260W |
| VRAM | 80-94 GB | 24 GB |
| CUDA Cores | 16,896 | 4,608 |
| Memory Type | HBM3 | GDDR6 |
| Architecture | Hopper | Turing |
| Form Factors | SXM5, PCIe, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | NVLink |
| Tensor Cores | 528 | 576 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 16.3 TFLOPS |
| FP32 Performance | 67 TFLOPS | 16.3 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 3,350 GB/s | 672 GB/s |
Performance Analysis
The H100's FP16 performance of 1979 TFLOPS vastly outpaces the Quadro RTX 6000's 16.3 TFLOPS, enabling faster AI training where half-precision computations dominate. For inference, the H100's FP8 capability at 3958 TFLOPS supports ultra-efficient deployment of massive models, while the Quadro lacks FP8 support entirely. The H100's FP32 at 67 TFLOPS remains superior to the Quadro's 16.3 TFLOPS, benefiting simulation workloads.
Memory bandwidth defines practical limits: the H100's 3350 GB/s allows batch sizes up to 10 times larger than the Quadro's 672 GB/s capacity, reducing training iterations for LLMs with billions of parameters. Higher VRAM on the H100, at 80-94 GB versus 24 GB, prevents out-of-memory errors in fine-tuning or inference on models exceeding 20 GB. Power draw reflects this: 700W TDP for H100 versus 260W for Quadro, suiting data centers over edge devices.
Interconnects further the gap: H100 supports NVLink, PCIe 5.0, and InfiniBand for multi-GPU scaling, while Quadro limits to NVLink and PCIe, constraining cluster efficiency.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Hyperstack | 4×NVIDIA H100 PCIe 80GB VRAM | 80GB | 124 vCPU 720GB RAM 3300GB Storage | Canada | $1.90/GPU/hr $7.60/hr total (4×) | Available | ||
Hyperstack | 2×NVIDIA H100 PCIe 80GB VRAM | 80GB | 60 vCPU 360GB RAM 1600GB Storage | Canada | $1.90/GPU/hr $3.80/hr total (2×) | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.90/GPU/hr $15.20/hr total (8×) | Available | ||
Hyperstack | NVIDIA H100 PCIe 80GB VRAM | 80GB | 28 vCPU 180GB RAM 850GB Storage | Canada | $1.90/GPU/hr | Available | ||
 Voltage Park | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 928GB RAM 19200GB Storage | Dallas, Texas | $1.99/GPU/hr $15.92/hr total (8×) |
When to Choose the H100
The H100 excels in AI-driven workloads requiring extreme compute and memory. Users training LLMs benefit from 1979 TFLOPS FP16 and 80-94 GB VRAM, handling models up to 70B parameters without distillation. Cloud availability from $0.80 per hour across 56 providers makes it ideal for scalable inference at 3958 TFLOPS FP8.
When to Choose the Quadro RTX 6000
The Quadro RTX 6000 suits legacy workstation applications with power constraints. Its 260W TDP fits standard desktops, unlike the H100's 700W demand. Professionals in CAD or rendering leverage 24 GB GDDR6 for tasks under 16.3 TFLOPS FP32, especially where on-premises hardware avoids cloud costs since no live offers exist.
Use Cases
H100's 1979 TFLOPS FP16 and 80-94 GB HBM3 enable training of large models with high batch sizes, far beyond Quadro's 16.3 TFLOPS and 24 GB.
3958 TFLOPS FP8 on H100 supports efficient serving of massive LLMs, while Quadro lacks FP8 and sufficient VRAM for models over 20 GB.
3350 GB/s bandwidth and 80-94 GB VRAM on H100 handle large datasets without OOM, outperforming Quadro's 672 GB/s and 24 GB.
H100's FP16 at 1979 TFLOPS accelerates image generation pipelines with bigger batches, versus Quadro's limited 16.3 TFLOPS.
67 TFLOPS FP32 and PCIe 5.0/NVLink on H100 scale simulations better than Quadro's 16.3 TFLOPS and basic PCIe.
Frequently Asked Questions
What is the VRAM capacity of H100 versus Quadro RTX 6000?▾
The H100 offers 80-94 GB HBM3 VRAM. The Quadro RTX 6000 provides 24 GB GDDR6. This gap allows H100 to manage models four times larger.
How do FP16 performances compare?▾
H100 delivers 1979 TFLOPS FP16. Quadro RTX 6000 achieves 16.3 TFLOPS FP16. H100 provides over 120 times the half-precision throughput for AI tasks.
What are the memory bandwidth differences?▾
H100 reaches 3350 GB/s. Quadro RTX 6000 offers 672 GB/s. Higher bandwidth on H100 supports larger batch sizes in training.
Is cloud pricing available for these GPUs?▾
H100 starts at $0.80 per hour, averaging $3.21 per hour across 56 offers. Quadro RTX 6000 has no live cloud offers.
What are the TDP ratings?▾
H100 requires 700W TDP. Quadro RTX 6000 uses 260W TDP. Lower power suits Quadro for workstations.
Which has better interconnects?▾
H100 supports NVLink, PCIe 5.0, and InfiniBand. Quadro RTX 6000 limits to NVLink and PCIe. H100 enables superior multi-GPU scaling.
Which is cheaper to rent, the H100 or the Quadro RTX 6000?▾
Cloud rental prices for both the H100 and Quadro RTX 6000 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 Quadro RTX 6000?▾
The H100 has 80 to 94 GB of HBM3 memory. The Quadro RTX 6000 has 24 GB of GDDR6 memory.
Can I find H100 and Quadro RTX 6000 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 Quadro RTX 6000?▾
The H100 uses the Hopper architecture (2022) while the Quadro RTX 6000 uses Turing (2018). The H100 delivers 121.4x the FP16 throughput and 5.0x the memory bandwidth of the Quadro RTX 6000.