How Much Power Does the NVIDIA Tesla V100 Consume?

The NVIDIA Tesla V100 GPU consumes between 250W and 350W depending on its variant.​

PCIe variant: 250W TDP
SXM2/NVLink variant: 300W TDP
32GB SXM3 variant: up to 350W TDP
Actual usage varies by workload, with peaks near TDP during AI training and lower draw for idle or inference tasks.​

Overview

The NVIDIA Tesla V100, launched on the Volta architecture, powers AI, HPC, and data analytics with Tensor Cores for mixed-precision computing. Its power consumption, measured as Thermal Design Power (TDP), differs by form factor to suit server environments. PCIe models target standard racks at 250W, while SXM2 modules for high-density NVLink systems hit 300W, and the memory-upgraded 32GB SXM3 reaches 350W for sustained high loads.​

Cyfuture Cloud deploys these GPUs in optimized clusters, using liquid cooling to handle dense configurations without excess data center power overhead. Dynamic modes like Maximum Performance (full TDP) and Maximum Efficiency (capped for 80% output at reduced draw) allow tuning for cost or speed.​

Variant Breakdown

Power ratings align with physical design and interconnects:

Higher TDP variants boost performance—e.g., 450W experimental models offer 16% more flops over 250W bases—but Cyfuture Cloud sticks to standard ratings for reliability. Power connectors include CPU 8-pin or PCIe 8/6-pin dongles, ensuring compatibility with enterprise PSUs.​

Factors Affecting Consumption

Real-world draw fluctuates below TDP based on tasks. AI training or simulations hit near-max (e.g., 300W+), while inference drops to 150-200W. Features like MIG (Multi-Instance GPU) partition resources, improving power efficiency by 40% in rack-scale setups versus CPU alternatives.​

Cyfuture Cloud enhances this with pay-per-use scaling and fine-tuned clusters, minimizing waste. Max-Q modes optimize performance-per-watt, vital for cloud economics where power is 30-50% of GPU hosting costs.​

Cyfuture Cloud Integration

Cyfuture Cloud offers V100 dedicated servers with transparent power-inclusive pricing, supporting all variants via passive/passive-liquid cooling. Hourly rates factor TDP directly, with MIG for multi-tenant efficiency. Liquid-cooled racks cut overall draw by 20-30% versus air-cooled peers, ideal for Delhi-based users scaling AI workloads.​

Conclusion

NVIDIA Tesla V100 power ranges from 250W PCIe to 350W SXM3, balancing Volta's breakthrough compute with manageable thermal needs. Cyfuture Cloud maximizes value through efficiency modes, partitioning, and scalable infrastructure—deploy today for AI/HPC without power surprises. Transitioning to cloud V100 cuts capex while optimizing opex.​

Follow-Up Questions

Q: What's the idle power draw?
A: Idle consumption sits at 20-50W across variants, depending on PCIe/SXM config and firmware.​

Q: Is V100 suitable for edge deployments?
A: No—high TDP limits edge use; opt for T4 (70W) or A10 for low-power inference.​

Q: How does Cyfuture Cloud optimize V100 power?
A: Via MIG partitioning, dynamic modes, liquid cooling, and usage-based scaling for 40% rack efficiency gains.​

Q: What's the V100 GPU price including power costs?
A: Varies by config; Cyfuture Cloud hourly rates bundle power transparently—contact for quotes.​

Q: How does V100 compare power-wise to A100?
A: A100 SXM (400W+) exceeds V100's 350W max but offers 2-3x performance; V100 suits legacy cost-sensitive loads.​