Specifications Compared
| Spec | RTX-2060 | V100 |
|---|---|---|
| TDP | 160W | 300W |
| VRAM | 6-12 GB | 16-32 GB |
| CUDA Cores | 1,920 | 5,120 |
| Memory Type | GDDR6 | HBM2 |
| Architecture | Turing | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink, PCIe 3.0 | |
| Tensor Cores | 240 | 640 |
| FP16 Performance | 6.5 TFLOPS | 125 TFLOPS |
| FP32 Performance | 6.5 TFLOPS | 15.7 TFLOPS |
| Memory Bandwidth | 336 GB/s | 900 GB/s |
Performance Analysis
The V100's FP16 performance dominates at 125 TFLOPS compared to 7.2 TFLOPS on the RTX 2060 Super: this 17-fold advantage accelerates mixed-precision training and inference for deep neural networks by orders of magnitude. FP32 capabilities follow suit, with V100's 15.7 TFLOPS more than doubling the 7.2 TFLOPS of RTX 2060 Super, aiding single-precision simulations and older models.
Memory differences prove pivotal for real-world workloads: V100's 32 GB HBM2 versus 8 GB GDDR6 enables batch sizes up to 64 for a 7B parameter model, versus 16 on RTX 2060 Super. The 900 GB/s bandwidth of V100 reduces latency in memory-bound operations like large matrix multiplications, compared to 448 GB/s on RTX 2060 Super. V100's 300 W TDP demands robust cooling, unlike the 175 W desktop-friendly RTX 2060 Super.
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 2060 SUPER
The RTX 2060 Super proves ideal for local, budget-limited machine learning experimentation. Its 8 GB VRAM and 448 GB/s bandwidth handle small model fine-tuning or Stable Diffusion generation with batch sizes up to 32, while 175 W TDP fits standard desktops without cloud dependency. Absence of live cloud offers favors outright purchase for persistent low-intensity use.
When to Choose the Tesla V100 32GB
The V100 32GB excels in demanding deep learning pipelines requiring high throughput. With 32 GB VRAM and 125 TFLOPS FP16, it supports large-batch LLM training unattainable on 8 GB RTX 2060 Super. Cloud availability from $0.29 per hour enables scalable access for production without hardware investment.
Use Cases
V100 32GB's 32 GB VRAM and 125 TFLOPS FP16 accommodate large LLMs with batch sizes over 32. RTX 2060 Super's 8 GB VRAM restricts it to tiny models.
V100's 900 GB/s bandwidth and 125 TFLOPS FP16 deliver high-throughput serving for production. RTX 2060 Super's 448 GB/s suits only low-volume inference.
RTX 2060 Super handles small models under 8 GB VRAM efficiently at 7.2 TFLOPS. V100 scales to larger ones with 32 GB and 15.7 TFLOPS FP32.
RTX 2060 Super's 8 GB GDDR6 and 448 GB/s bandwidth generate images locally with batch 16. V100 overkill for consumer creative tasks.
V100's 15.7 TFLOPS FP32 and 32 GB VRAM accelerate simulations with large datasets. RTX 2060 Super's 7.2 TFLOPS limits complex computations.
Frequently Asked Questions
Is the RTX 2060 Super better than V100 32GB for machine learning?▾
The V100 32GB outperforms with 125 TFLOPS FP16 and 32 GB HBM2 VRAM versus RTX 2060 Super's 7.2 TFLOPS and 8 GB GDDR6. It excels in training; RTX 2060 Super fits entry-level inference. V100 rents from $0.29 per hour.
What is the memory bandwidth difference between RTX 2060 Super and V100?▾
RTX 2060 Super offers 448 GB/s with 8 GB GDDR6. V100 provides 900 GB/s with 32 GB HBM2. This doubles effective throughput for data-intensive AI tasks on V100.
RTX 2060 Super FP32 performance vs V100?▾
RTX 2060 Super delivers 7.2 TFLOPS FP32. V100 achieves 15.7 TFLOPS FP32. V100 processes twice the single-precision FLOPs per second.
Can RTX 2060 Super replace V100 in cloud ML?▾
No live cloud offers exist for RTX 2060 Super. V100 32GB available from $0.29 per hour averaging $1.01 per hour across 46 offers. RTX 2060 Super suits local desktops only.
Power consumption: RTX 2060 Super vs V100 32GB?▾
RTX 2060 Super TDP is 175 W for desktop use. V100 requires 300 W with datacenter cooling. Higher TDP enables V100's 125 TFLOPS FP16.
Which has more VRAM: RTX 2060 Super or V100 32GB?▾
V100 32GB has 32 GB HBM2. RTX 2060 Super provides 8 GB GDDR6. V100 supports four times larger models or batches.
Which is cheaper to rent, the RTX 2060 or the V100?▾
Cloud rental prices for both the RTX 2060 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 2060 have compared to the V100?▾
The RTX 2060 has 6 to 12 GB of GDDR6 memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find RTX 2060 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 2060 and the V100?▾
The RTX 2060 uses the Turing architecture (2019) while the V100 uses Volta (2017). The V100 delivers 19.2x the FP16 throughput and 2.7x the memory bandwidth of the RTX 2060.