Specifications Compared
| Spec | QUADRO-P4000 | V100 |
|---|---|---|
| TDP | 105W | 300W |
| VRAM | 8 GB | 16-32 GB |
| CUDA Cores | 1,792 | 5,120 |
| Memory Type | GDDR5 | HBM2 |
| Architecture | Pascal | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink, PCIe 3.0 | |
| FP16 Performance | 5.3 TFLOPS | 125 TFLOPS |
| FP32 Performance | 5.3 TFLOPS | 15.7 TFLOPS |
| Memory Bandwidth | 243 GB/s | 900 GB/s |
Performance Analysis
The V100's FP16 performance reaches 125 TFLOPS, dwarfing the P4000's 5.3 TFLOPS: this accelerates mixed-precision training where models use half-precision for speed without much accuracy loss. FP32 capabilities show V100 at 15.7 TFLOPS against 5.3 TFLOPS, benefiting single-precision tasks like traditional simulations. In real-world training, V100 handles larger models faster due to these metrics.
Memory bandwidth of 900 GB/s on V100 versus 243 GB/s on P4000 enables substantially larger batch sizes, reducing per-iteration overhead in deep learning pipelines. The 32 GB HBM2 VRAM on V100 supports datasets and models exceeding 8 GB GDDR5 limits of P4000, preventing out-of-memory errors in inference or fine-tuning. Bandwidth superiority minimizes data transfer bottlenecks during compute-intensive phases.
TDP impacts deployment: P4000's 105W allows more units per server, but V100's 300W and NVLink justify it for multi-GPU training where scaling yields higher effective throughput.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
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 |
Tesla V100 32GB
| 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 P4000
The Quadro P4000 excels in power-constrained environments: its 105W TDP compared to 300W on V100 supports denser cloud instances and lower cooling costs. At an average $0.51 per hour across 6 offers, it fits budget visualization, CAD rendering, or light inference tasks where 8 GB VRAM and 5.3 TFLOPS suffice without needing HBM2 speeds.
When to Choose the Tesla V100 32GB
The Tesla V100 32GB dominates AI and HPC workloads: 125 TFLOPS FP16 and 32 GB VRAM handle large-scale LLM training or scientific simulations infeasible on P4000's 5.3 TFLOPS and 8 GB. NVLink interconnect enables efficient multi-GPU scaling, with 900 GB/s bandwidth supporting massive batch sizes despite 300W TDP.
Use Cases
V100's 32 GB HBM2 VRAM and 125 TFLOPS FP16 support large language models that exceed P4000's 8 GB GDDR5 capacity. The 900 GB/s bandwidth handles high-throughput training batches efficiently.
V100 delivers 125 TFLOPS FP16 for rapid inference on big models, far beyond P4000's 5.3 TFLOPS. Its 32 GB VRAM accommodates multiple concurrent requests without swapping.
Fine-tuning benefits from V100's 15.7 TFLOPS FP32 and 900 GB/s bandwidth for optimized batch processing. P4000's 243 GB/s limits scalability on datasets over 8 GB.
Stable Diffusion requires substantial VRAM for high-resolution generation: V100's 32 GB outperforms P4000's 8 GB. FP16 performance at 125 TFLOPS speeds diffusion steps dramatically.
V100's 15.7 TFLOPS FP32 and NVLink suit parallel simulations better than P4000's 5.3 TFLOPS. Higher bandwidth of 900 GB/s reduces data movement delays in complex computations.
Frequently Asked Questions
Which GPU has more VRAM?▾
The NVIDIA Tesla V100 32GB provides 32 GB HBM2, doubling or quadrupling the Quadro P4000's 8 GB GDDR5. This allows V100 to load larger models for training or inference. P4000 suits smaller workloads within its memory limit.
What are the FP32 performance differences?▾
V100 achieves 15.7 TFLOPS FP32, nearly tripling P4000's 5.3 TFLOPS. This impacts general-purpose computing and simulations requiring single precision. V100 processes more operations per second in FP32-bound tasks.
How do memory bandwidths compare?▾
V100 offers 900 GB/s bandwidth with HBM2, over three times P4000's 243 GB/s GDDR5. Higher bandwidth supports larger batch sizes in ML training. It reduces bottlenecks in data-heavy applications.
What is the power consumption difference?▾
P4000 has a 105W TDP, much lower than V100's 300W. Lower TDP enables more efficient deployments in power-limited clouds. V100 trades efficiency for superior compute density.
Which is cheaper in the cloud?▾
P4000 averages $0.51 per hour across 6 offers, while V100 starts at $0.29 per hour but averages $1.01 across 46 offers. Pricing varies by provider and instance. V100 often provides better value for high-performance needs.
Do they support multi-GPU setups?▾
Both offer PCIe form factors, but V100 adds SXM2 and NVLink for faster interconnects. NVLink enhances scaling in multi-GPU training over P4000's standard PCIe. This benefits distributed workloads on V100.
Which is cheaper to rent, the Quadro P4000 or the V100?▾
Cloud rental prices for both the Quadro P4000 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 P4000 have compared to the V100?▾
The Quadro P4000 has 8 GB of GDDR5 memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find Quadro P4000 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 P4000 and the V100?▾
The Quadro P4000 uses the Pascal architecture (2017) while the V100 uses Volta (2017). The V100 delivers 23.6x the FP16 throughput and 3.7x the memory bandwidth of the Quadro P4000.