Specifications Compared
| Spec | H100 | QUADRO-P4000 |
|---|---|---|
| TDP | 700W | 105W |
| VRAM | 80-94 GB | 8 GB |
| CUDA Cores | 16,896 | 1,792 |
| Memory Type | HBM3 | GDDR5 |
| Architecture | Hopper | Pascal |
| Form Factors | SXM5, PCIe, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| Tensor Cores | 528 | |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 5.3 TFLOPS |
| FP32 Performance | 67 TFLOPS | 5.3 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 3,350 GB/s | 243 GB/s |
Performance Analysis
The H100 PCIe dominates in FP16 performance at 1979 TFLOPS compared to the Quadro P4000's 5.3 TFLOPS, accelerating AI training where half-precision arithmetic prevails and reducing epochs from days to hours. Its FP32 rate of 67 TFLOPS, 12.6 times the P4000's 5.3 TFLOPS, supports inference and simulations needing full single-precision. FP8 capability at 3958 TFLOPS on H100 further optimizes quantized inference, unavailable on P4000.
Memory bandwidth of 3350 GB/s on H100 versus 243 GB/s on P4000 allows larger batch sizes in training, minimizing data loading bottlenecks and improving throughput by over 13 times. P4000 suits small-batch legacy tasks but bottlenecks on modern models exceeding 8 GB VRAM. TDP disparity, 700W for H100 and 105W for P4000, implies higher power draw for H100 but enables denser compute in clusters via PCIe 5.0.
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 | |
|---|---|---|---|---|---|---|---|---|
 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 | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.95/GPU/hr $15.60/hr total (8×) | Available |
Quadro P4000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Paperspace | NVIDIA Quadro P4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | Canada | $0.51/GPU/hr | Available | ||
Paperspace | 2×NVIDIA Quadro P4000 8GB VRAM | 8GB | 16 vCPU 60GB RAM 50GB Storage | New York | $0.51/GPU/hr $1.02/hr total (2×) | Available | ||
Paperspace | 2×NVIDIA Quadro P4000 8GB VRAM | 8GB | 16 vCPU 60GB RAM 50GB Storage | Canada | $0.51/GPU/hr $1.02/hr total (2×) | Available | ||
Paperspace | NVIDIA Quadro P4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | Amsterdam | $0.51/GPU/hr | Available | ||
Paperspace | NVIDIA Quadro P4000 8GB VRAM | 8GB | 8 vCPU 30GB RAM 50GB Storage | New York | $0.51/GPU/hr | Available |
When to Choose the H100 PCIe
Select the H100 PCIe for large-scale machine learning tasks such as training LLMs or Stable Diffusion models, where 80 to 94 GB HBM3 VRAM accommodates models with billions of parameters. Its 1979 TFLOPS FP16 and 3350 GB/s bandwidth handle massive datasets and batch sizes efficiently, justifying $1.25 to $2.68 per hour in cloud deployments.
When to Choose the Quadro P4000
Opt for the Quadro P4000 in budget-constrained professional visualization like CAD or light rendering, where 8 GB GDDR5 and 5.3 TFLOPS suffice for single-user workflows. At $0.51 per hour and 105W TDP, it offers low-cost, low-power operation without needing H100's overkill for non-AI tasks.
Use Cases
H100's 80-94 GB VRAM and 1979 TFLOPS FP16 support massive models and large batches, unlike P4000's 8 GB limit.
3958 TFLOPS FP8 and 3350 GB/s bandwidth enable high-throughput serving; P4000 lacks capacity for production-scale inference.
67 TFLOPS FP32 and high VRAM fit adapter tuning on large models; P4000 restricts to tiny datasets.
H100 handles high-resolution generations with 1979 TFLOPS FP16; P4000's 243 GB/s bandwidth causes slowdowns.
67 TFLOPS FP32 outperforms P4000's 5.3 TFLOPS for simulations; vast VRAM aids complex datasets.
Frequently Asked Questions
What is the VRAM difference between H100 PCIe and Quadro P4000?▾
H100 PCIe offers 80 to 94 GB HBM3 VRAM, while Quadro P4000 has 8 GB GDDR5. This 10 to 11.75 times gap allows H100 to load entire large models in memory.
How do compute performances compare?▾
H100 delivers 1979 TFLOPS FP16 and 67 TFLOPS FP32 versus P4000's 5.3 TFLOPS in both. H100 provides 373 times FP16 speedup for AI tasks.
What are the cloud pricing differences?▾
H100 PCIe starts at $1.25 per hour, averaging $2.68 across 16 offers. Quadro P4000 is $0.51 per hour across 6 offers.
Is H100 better for AI training?▾
Yes, H100's 3350 GB/s bandwidth and 1979 TFLOPS FP16 enable large-batch training. P4000's 243 GB/s limits it to small-scale work.
What about power consumption?▾
H100 PCIe has 700W TDP for peak performance in clusters. P4000's 105W suits low-power desktop or edge use.
Can P4000 handle modern ML?▾
P4000's 8 GB VRAM and 5.3 TFLOPS restrict it to basic models. H100 excels with 80-94 GB for LLMs.
Which is cheaper to rent, the H100 or the Quadro P4000?▾
Cloud rental prices for both the H100 and Quadro P4000 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 P4000?▾
The H100 has 80 to 94 GB of HBM3 memory. The Quadro P4000 has 8 GB of GDDR5 memory.
Can I find H100 and Quadro P4000 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 P4000?▾
The H100 uses the Hopper architecture (2022) while the Quadro P4000 uses Pascal (2017). The H100 delivers 373.4x the FP16 throughput and 13.8x the memory bandwidth of the Quadro P4000.