Specifications Compared
| Spec | H200 | QUADRO-P6000 |
|---|---|---|
| TDP | 700W | 250W |
| VRAM | 141 GB | 24 GB |
| CUDA Cores | 16,896 | 3,840 |
| Memory Type | HBM3e | GDDR5X |
| Architecture | Hopper | Pascal |
| Form Factors | SXM, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| Tensor Cores | 528 | |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 12.6 TFLOPS |
| FP32 Performance | 67 TFLOPS | 12.6 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 4,800 GB/s | 432 GB/s |
Performance Analysis
The H200's 1979 TFLOPS FP16 performance towers over the P6000's 12.6 TFLOPS, accelerating deep learning training where half-precision computations prevail. Its 67 TFLOPS FP32 surpasses P6000's 12.6 TFLOPS, aiding scientific simulations in single precision. P6000's equal FP16 and FP32 rates hinder mixed-precision workflows common today.
H200's 4800 GB/s bandwidth enables enormous batch sizes for training billion-parameter models, while P6000's 432 GB/s creates bottlenecks with datasets exceeding 24 GB VRAM. The 141 GB capacity on H200 supports full-model loading for inference, versus P6000's limitations to smaller networks.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H200 NVL
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | Atlanta | $1.99/GPU/hr | Available | ||
 Lambda Labs | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 64 vCPU 432GB RAM 4096GB Storage | Virginia | $2.29/GPU/hr | Available | ||
 Nebius | NVIDIA H200 SXM 141GB VRAM | 141GB | 16 vCPU 200GB RAM | 🌍Europe | $2.45/GPU/hr | |||
 CoreWeave | 8×NVIDIA H200 SXM 141GB VRAM | 141GB | 128 vCPU 0GB RAM 61440GB Storage | United States | $2.58/GPU/hr $20.64/hr total (8×) | |||
 Ori | NVIDIA H200 SXM 141GB VRAM | 141GB | 24 vCPU 240GB RAM 3000GB Storage | London | $3.50/GPU/hr | Available |
Quadro P6000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Paperspace | NVIDIA Quadro P6000 24GB VRAM | 24GB | 8 vCPU 30GB RAM 50GB Storage | New York | $1.10/GPU/hr | Available | ||
Paperspace | NVIDIA Quadro P6000 24GB VRAM | 24GB | 8 vCPU 30GB RAM 50GB Storage | Amsterdam | $1.10/GPU/hr | Available | ||
Paperspace | NVIDIA Quadro P6000 24GB VRAM | 24GB | 8 vCPU 30GB RAM 50GB Storage | Canada | $1.10/GPU/hr | Available | ||
Paperspace | 2×NVIDIA Quadro P6000 24GB VRAM | 24GB | 16 vCPU 60GB RAM 50GB Storage | New York | $1.10/GPU/hr $2.20/hr total (2×) | Available | ||
Paperspace | 2×NVIDIA Quadro P6000 24GB VRAM | 24GB | 16 vCPU 60GB RAM 50GB Storage | Amsterdam | $1.10/GPU/hr $2.20/hr total (2×) | Available |
When to Choose the H200 NVL
The H200 excels in large-scale AI: 1979 TFLOPS FP16 and 141 GB VRAM manage LLM training with batch sizes infeasible on P6000's 12.6 TFLOPS and 24 GB. Its 4800 GB/s bandwidth and NVLink interconnect optimize multi-GPU clusters at $0.50 per hour starting price.
When to Choose the Quadro P6000
Select the Quadro P6000 for legacy professional visualization: 250W TDP and PCIe form factor integrate easily into workstations. At $1.10 per hour, it suffices for CAD or rendering tasks under 24 GB VRAM without needing H200's 700W power draw.
Use Cases
H200's 1979 TFLOPS FP16 and 141 GB VRAM support massive models and large batches. P6000's 12.6 TFLOPS and 24 GB VRAM fall short.
3958 TFLOPS FP8 and 4800 GB/s bandwidth on H200 deliver low-latency serving for huge models. P6000 lacks capacity.
67 TFLOPS FP32 and high bandwidth handle parameter-efficient methods efficiently. P6000's specs limit scale.
141 GB VRAM fits full diffusion pipelines; 1979 TFLOPS FP16 speeds generation. P6000 bottlenecks at 24 GB.
67 TFLOPS FP32 outperforms P6000's 12.6 TFLOPS for simulations. Bandwidth aids large datasets.
Frequently Asked Questions
What is the VRAM capacity of NVIDIA H200 versus Quadro P6000?▾
H200 provides 141 GB HBM3e VRAM. Quadro P6000 offers 24 GB GDDR5X. This gap allows H200 to accommodate models over 100 GB.
How do FP16 performances compare between H200 and P6000?▾
H200 delivers 1979 TFLOPS FP16. P6000 achieves 12.6 TFLOPS. H200 accelerates training by over 150 times.
What are the memory bandwidth differences?▾
H200 reaches 4800 GB/s. P6000 provides 432 GB/s. Higher bandwidth on H200 supports larger batches.
What is the TDP for each GPU?▾
H200 requires 700W TDP. P6000 uses 250W. P6000 suits lower-power setups.
How do cloud prices compare?▾
H200 NVL starts at $0.50 per hour, averaging $2.60 across five offers. P6000 is $1.10 per hour across six offers.
What architectures power these GPUs?▾
H200 uses Hopper from 2024. P6000 employs Pascal from 2016. The eight-year gap explains performance disparities.
Which is cheaper to rent, the H200 or the Quadro P6000?▾
Cloud rental prices for both the H200 and Quadro P6000 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 H200 have compared to the Quadro P6000?▾
The H200 has 141 GB of HBM3e memory. The Quadro P6000 has 24 GB of GDDR5X memory.
Can I find H200 and Quadro P6000 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 H200 and the Quadro P6000?▾
The H200 uses the Hopper architecture (2024) while the Quadro P6000 uses Pascal (2016). The H200 delivers 157.1x the FP16 throughput and 11.1x the memory bandwidth of the Quadro P6000.