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 V100 dominates in raw compute: its 125 TFLOPS FP16 capability vastly exceeds the RTX 2070's 7.5 TFLOPS, enabling faster mixed-precision training for deep learning models where FP16 accelerates matrix operations without substantial accuracy loss. FP32 performance at 15.7 TFLOPS on the V100 doubles the RTX 2070's 7.5 TFLOPS, benefiting single-precision scientific simulations or inference pipelines requiring precise floating-point arithmetic.
Memory bandwidth presents a clear gap: the V100's 900 GB/s HBM2 allows larger batch sizes in training, reducing overhead and improving throughput for memory-bound tasks like transformer models, while the RTX 2070's 448 GB/s GDDR6 limits it to smaller batches. The V100's 32 GB VRAM supports datasets or models up to four times larger than the RTX 2070's 8 GB, preventing out-of-memory errors in large-scale inference or fine-tuning.
Power efficiency favors the RTX 2070 at 175W TDP versus 300W, suiting edge or low-cost cloud instances, but the V100's PCIe and SXM2 form factors with NVLink excel in clustered high-performance computing.
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
The RTX 2070 suits budget-conscious users for lightweight machine learning inference or small-scale fine-tuning, where its 8 GB VRAM and 7.5 TFLOPS FP32 handle models under 1 billion parameters efficiently. At $0.02 per hour minimum pricing, it delivers value for prototyping or hobbyist Stable Diffusion runs, avoiding the V100's higher 300W TDP and $0.29 per hour cost.
Low-power PCIe form factor makes it ideal for single-GPU cloud instances with limited cooling or electricity budgets.
When to Choose the Tesla V100 32GB
The V100 excels in demanding AI training workloads leveraging its 125 TFLOPS FP16 and 32 GB HBM2 VRAM, supporting large language models or batch sizes infeasible on the RTX 2070's 8 GB GDDR6. Its 900 GB/s bandwidth and NVLink interconnect optimize multi-GPU scaling for production environments.
Enterprise users prioritize the V100's 15.7 TFLOPS FP32 for scientific computing despite the 300W TDP and $1.01 per hour average, given 46 live cloud offers.
Use Cases
The V100's 125 TFLOPS FP16 and 32 GB HBM2 VRAM handle large transformer models and high batch sizes effectively. The RTX 2070's 8 GB VRAM limits scalability.
V100's 900 GB/s bandwidth supports high-throughput inference for production LLMs. RTX 2070 suffices only for tiny models due to 448 GB/s and 8 GB VRAM constraints.
V100's 15.7 TFLOPS FP32 and 32 GB VRAM accommodate dataset-heavy fine-tuning. RTX 2070 risks memory errors with its 8 GB limit.
RTX 2070's 7.5 TFLOPS FP16 and low $0.02 per hour cost fit image generation at 512x512 resolutions. V100 overkill for consumer-scale diffusion.
V100's 15.7 TFLOPS FP32 outperforms RTX 2070's 7.5 TFLOPS for simulations. NVLink aids multi-GPU HPC clusters.
Frequently Asked Questions
Which GPU has more VRAM?▾
The NVIDIA Tesla V100 32GB provides 32 GB HBM2 VRAM, quadrupling the RTX 2070's 8 GB GDDR6. This enables larger models on the V100. RTX 2070 suits smaller workloads.
What is the FP16 performance difference?▾
V100 delivers 125 TFLOPS FP16, over 16 times the RTX 2070's 7.5 TFLOPS. This accelerates mixed-precision training significantly on V100. RTX 2070 lags in AI acceleration.
How do cloud prices compare?▾
RTX 2070 starts at $0.02 per hour (average $0.04 across 2 offers), versus V100 32GB at $0.29 per hour (average $1.01 across 46 offers). RTX 2070 wins on cost. V100 justifies expense for performance.
Which has higher memory bandwidth?▾
V100 offers 900 GB/s HBM2 bandwidth, doubling RTX 2070's 448 GB/s GDDR6. Larger batches are possible on V100. RTX 2070 limits memory-intensive tasks.
What are the TDP ratings?▾
RTX 2070 consumes 175W TDP, lower than V100's 300W. This favors RTX 2070 in power-constrained clouds. V100 requires robust cooling.
Do both support NVLink?▾
Both GPUs feature NVLink interconnect for multi-GPU communication. V100 adds PCIe 3.0 options via SXM2 or PCIe forms. RTX 2070 uses PCIe primarily.
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.