Specifications Compared
| Spec | RTX-2070 | V100 |
|---|---|---|
| TDP | 175W | 300W |
| VRAM | 8 GB | 16-32 GB |
| CUDA Cores | 2,304 | 5,120 |
| Memory Type | GDDR6 | HBM2 |
| Architecture | Turing | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink | NVLink, PCIe 3.0 |
| Tensor Cores | 288 | 640 |
| FP16 Performance | 7.5 TFLOPS | 125 TFLOPS |
| FP32 Performance | 7.5 TFLOPS | 15.7 TFLOPS |
| Memory Bandwidth | 448 GB/s | 900 GB/s |
Performance Analysis
The FP16 performance disparity defines key workloads: the V100 reaches 125 TFLOPS, enabling up to 14 times faster mixed-precision training and inference compared to the RTX 2070 SUPER's 9 TFLOPS. This accelerates deep learning models where tensor cores dominate, reducing training times for neural networks.
FP32 rates show V100 at 15.7 TFLOPS versus 9 TFLOPS, favoring V100 for simulation and general compute yet remaining competitive. Memory bandwidth of 900 GB/s on V100 supports larger batch sizes and higher throughput than 448 GB/s, minimizing data transfer bottlenecks in training large models. The 32 GB VRAM versus 8 GB allows V100 to handle bigger models without swapping, while 215 W TDP on 2070 SUPER eases power constraints in home setups.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
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 RTX 2070 SUPER
The RTX 2070 SUPER excels in budget desktop environments for gaming combined with light AI inference. Its 8 GB VRAM and 448 GB/s bandwidth suffice for Stable Diffusion or small model fine-tuning, and 215 W TDP fits standard power supplies without cloud dependency. Users avoid rental costs since no live cloud offers exist.
When to Choose the Tesla V100 32GB
Select the V100 32GB for demanding AI training requiring 125 TFLOPS FP16 and 32 GB VRAM to process large LLMs. Cloud pricing from $0.29 per hour across 46 offers provides scalability, and 900 GB/s bandwidth enables efficient large-batch processing. NVLink interconnect supports multi-GPU setups unavailable on consumer cards.
Use Cases
V100's 125 TFLOPS FP16 and 32 GB HBM2 VRAM manage large language models effectively. RTX 2070 SUPER's 8 GB VRAM limits batch sizes.
V100 handles high-throughput inference with 900 GB/s bandwidth and 125 TFLOPS FP16. 2070 SUPER suits only small-scale deployments.
32 GB VRAM on V100 supports larger fine-tuning datasets than 8 GB on 2070 SUPER. FP16 advantage speeds iterations.
RTX 2070 SUPER's 9 TFLOPS FP32 and 448 GB/s bandwidth generate images adequately for personal use. Lower 215 W TDP fits desktops.
V100's 15.7 TFLOPS FP32 and NVLink excel in HPC simulations. Higher bandwidth aids data-intensive computations.
Frequently Asked Questions
Which has more VRAM: RTX 2070 SUPER or V100 32GB?▾
The V100 32GB offers 32 GB HBM2 VRAM, quadrupling the RTX 2070 SUPER's 8 GB GDDR6. This enables larger models on V100. Bandwidth also favors V100 at 900 GB/s over 448 GB/s.
How does FP16 performance compare between RTX 2070 SUPER and V100?▾
V100 delivers 125 TFLOPS FP16, far exceeding RTX 2070 SUPER's 9 TFLOPS. This boosts AI training speed on V100. FP32 is 15.7 TFLOPS versus 9 TFLOPS.
What is the power consumption of these GPUs?▾
RTX 2070 SUPER has a 215 W TDP, lower than V100's 300 W. This makes 2070 SUPER easier for home builds. V100 suits datacenters with cooling.
Is V100 available on cloud for RTX 2070 SUPER users?▾
V100 32GB clouds from $0.29 per hour average $1.01 across 46 offers. RTX 2070 SUPER has no live cloud offers. Rent V100 for pro workloads.
Which GPU wins for AI training?▾
V100 dominates with 125 TFLOPS FP16 and 32 GB VRAM for training. RTX 2070 SUPER's 9 TFLOPS limits it to entry-level tasks. Bandwidth 900 GB/s aids V100 batches.
What architectures do they use?▾
RTX 2070 SUPER uses Turing from 2019; V100 uses Volta from 2017. V100's datacenter focus yields higher FP16 at 125 TFLOPS. 2070 SUPER targets consumers.
Which is cheaper to rent, the RTX 2070 or the V100?▾
Cloud rental prices for both the RTX 2070 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 RTX 2070 have compared to the V100?▾
The RTX 2070 has 8 GB of GDDR6 memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find RTX 2070 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 RTX 2070 and the V100?▾
The RTX 2070 uses the Turing architecture (2018) while the V100 uses Volta (2017). The V100 delivers 16.7x the FP16 throughput and 2.0x the memory bandwidth of the RTX 2070.