Specifications Compared
| Spec | QUADRO-P5000 | V100 |
|---|---|---|
| TDP | 180W | 300W |
| VRAM | 16 GB | 16-32 GB |
| CUDA Cores | 2,560 | 5,120 |
| Memory Type | GDDR5X | HBM2 |
| Architecture | Pascal | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink, PCIe 3.0 | |
| FP16 Performance | 8.9 TFLOPS | 125 TFLOPS |
| FP32 Performance | 8.9 TFLOPS | 15.7 TFLOPS |
| Memory Bandwidth | 288 GB/s | 900 GB/s |
Performance Analysis
The V100 dominates in compute performance: its FP16 reaches 125 TFLOPS, over 14 times the P5000's 8.9 TFLOPS, accelerating mixed-precision training in deep learning frameworks. FP32 performance on the V100 hits 15.7 TFLOPS, nearly doubling the P5000's 8.9 TFLOPS, benefiting single-precision scientific simulations and inference. This FP16 to FP32 delta on the V100 enables efficient training of large models with half-precision, reducing memory usage by 50 percent while maintaining accuracy, unlike the P5000's balanced but lower throughput. Memory bandwidth reveals another gap: the V100's 900 GB/s HBM2 supports batch sizes three times larger than the P5000's 288 GB/s GDDR5X, minimizing data bottlenecks in transformer models or CNNs during training. Higher TDP of 300W on the V100 sustains peak performance longer than the P5000's 180W, though it demands robust cooling in cloud environments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
Quadro P5000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Paperspace | 2×NVIDIA Quadro P5000 16GB VRAM | 16GB | 16 vCPU 60GB RAM 50GB Storage | Amsterdam | $0.78/GPU/hr $1.56/hr total (2×) | Available | ||
Paperspace | 2×NVIDIA Quadro P5000 16GB VRAM | 16GB | 16 vCPU 60GB RAM 50GB Storage | Canada | $0.78/GPU/hr $1.56/hr total (2×) | Available | ||
Paperspace | 2×NVIDIA Quadro P5000 16GB VRAM | 16GB | 16 vCPU 60GB RAM 50GB Storage | New York | $0.78/GPU/hr $1.56/hr total (2×) | Available | ||
Paperspace | NVIDIA Quadro P5000 16GB VRAM | 16GB | 8 vCPU 30GB RAM 50GB Storage | Amsterdam | $0.78/GPU/hr | Available | ||
Paperspace | NVIDIA Quadro P5000 16GB VRAM | 16GB | 8 vCPU 30GB RAM 50GB Storage | New York | $0.78/GPU/hr | Available |
Tesla V100 16GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Texas | $0.19/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 0 vCPU 0GB RAM | New York City | $0.19/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 32GB 32GB VRAM | 32GB | 0 vCPU 0GB RAM | Texas | $0.29/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 32GB 32GB VRAM | 32GB | 0 vCPU 0GB RAM | New York City | $0.29/GPU/hr | Available | ||
 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 |
When to Choose the Quadro P5000
The Quadro P5000 fits legacy workstation applications like CAD rendering or professional visualization where Pascal optimizations provide stability. Its 180W TDP consumes less power than the V100's 300W, reducing costs in low-density cloud instances at $0.78 per hour average. Fewer interconnect demands via PCIe alone suit non-parallel workloads without NVLink needs.
When to Choose the Tesla V100 16GB
The Tesla V100 excels in AI training and HPC tasks leveraging its 125 TFLOPS FP16 and 900 GB/s bandwidth for large datasets. NVLink interconnect enables multi-GPU scaling unavailable on the P5000, ideal for distributed training. Cloud availability across 25 offers starting at $0.10 per hour offers flexibility for high-throughput jobs.
Use Cases
V100's 125 TFLOPS FP16 enables fast mixed-precision training of large language models, far exceeding P5000's 8.9 TFLOPS. Its 900 GB/s bandwidth handles massive datasets without bottlenecks.
High FP16 throughput of 125 TFLOPS on V100 accelerates batched inference for LLMs. NVLink supports multi-GPU serving, unlike P5000's PCIe limitations.
V100's 15.7 TFLOPS FP32 and 125 TFLOPS FP16 optimize fine-tuning efficiency. Superior 900 GB/s bandwidth supports larger batch sizes than P5000's 288 GB/s.
FP16 performance of 125 TFLOPS on V100 speeds diffusion model generation. HBM2 memory sustains high-resolution image tasks better than P5000's GDDR5X.
V100's 15.7 TFLOPS FP32 outperforms P5000's 8.9 TFLOPS for simulations. NVLink interconnect scales computations across nodes effectively.
Frequently Asked Questions
Which GPU has higher FP16 performance?▾
The V100 achieves 125 TFLOPS FP16, compared to the P5000's 8.9 TFLOPS. This 14-fold difference favors V100 for half-precision AI tasks. Bandwidth also triples to 900 GB/s on V100.
What is the memory bandwidth difference?▾
V100 provides 900 GB/s with HBM2, over three times the P5000's 288 GB/s GDDR5X. Larger batches fit in training due to this gap. Both offer 16 GB VRAM.
How do cloud prices compare?▾
P5000 averages $0.78 per hour across 6 offers, while V100 16GB averages $0.81 per hour across 25 offers from $0.10 per hour. V100 has more availability. Pricing suits varied budgets.
Which has lower power consumption?▾
P5000 draws 180W TDP versus V100's 300W. Lower power aids dense deployments. V100 sustains higher 125 TFLOPS FP16 despite increased draw.
Is V100 compatible with multi-GPU setups?▾
V100 supports NVLink and PCIe 3.0 for interconnects, enabling scaling. P5000 limits to PCIe only. This aids distributed training on V100.
What architectures do they use?▾
P5000 uses Pascal from 2016 with balanced 8.9 TFLOPS FP16 and FP32. V100 employs Volta from 2017 with 125 TFLOPS FP16 and 15.7 TFLOPS FP32. Volta targets datacenter AI.
Which is cheaper to rent, the Quadro P5000 or the V100?▾
Cloud rental prices for both the Quadro P5000 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 Quadro P5000 have compared to the V100?▾
The Quadro P5000 has 16 GB of GDDR5X memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find Quadro P5000 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 Quadro P5000 and the V100?▾
The Quadro P5000 uses the Pascal architecture (2016) while the V100 uses Volta (2017). The V100 delivers 14.0x the FP16 throughput and 3.1x the memory bandwidth of the Quadro P5000.