Specifications Compared
| Spec | RTX-4060 | V100 |
|---|---|---|
| TDP | 115W | 300W |
| VRAM | 8 GB | 16-32 GB |
| CUDA Cores | 3,072 | 5,120 |
| Memory Type | GDDR6 | HBM2 |
| Architecture | Ada Lovelace | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink, PCIe 3.0 | |
| Tensor Cores | 96 | 640 |
| FP16 Performance | 15.1 TFLOPS | 125 TFLOPS |
| FP32 Performance | 15.1 TFLOPS | 15.7 TFLOPS |
| INT8 Performance | 242 TOPS | |
| Memory Bandwidth | 272 GB/s | 900 GB/s |
Performance Analysis
The V100 dominates in FP16 performance at 125 TFLOPS compared to the RTX 4060 Ti's 15.1 TFLOPS: this gap accelerates deep learning training using mixed precision, enabling faster convergence on large models. FP32 throughput remains close with 15.7 TFLOPS on the V100 and 15.1 TFLOPS on the RTX 4060 Ti, suiting single-precision inference tasks equally well. Memory bandwidth of 900 GB/s on the V100 versus 272 GB/s on the RTX 4060 Ti supports larger batch sizes without out-of-memory errors, crucial for training datasets exceeding 8 GB VRAM limits. The V100's 16 GB HBM2 handles bigger models than the RTX 4060 Ti's 8 GB GDDR6, reducing data transfer bottlenecks in memory-intensive simulations. Higher 300W TDP on the V100 reflects its compute focus, while the RTX 4060 Ti's 115W efficiency aids dense cloud deployments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
Tesla V100 16GB
| 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 4060 Ti
Opt for the RTX 4060 Ti in cost-sensitive scenarios like lightweight inference or development prototyping: its $0.08/hr starting price and $0.14/hr average beat the V100's $0.82/hr average, delivering FP32 at 15.1 TFLOPS for quick iterations. Low 115W TDP and PCIe form factor suit edge computing or multi-GPU setups without high power costs.
When to Choose the Tesla V100 16GB
Select the V100 16GB for demanding training workloads requiring high FP16 throughput of 125 TFLOPS: it outperforms the RTX 4060 Ti's 15.1 TFLOPS, speeding up model convergence. Superior 900 GB/s bandwidth and 16 GB VRAM enable large-batch training on complex models unavailable on the 8 GB RTX 4060 Ti.
Use Cases
V100's 125 TFLOPS FP16 vastly exceeds RTX 4060 Ti's 15.1 TFLOPS, accelerating mixed-precision training. Its 16 GB VRAM and 900 GB/s bandwidth handle large models better.
RTX 4060 Ti's 15.1 TFLOPS FP32 matches V100's 15.7 TFLOPS closely for inference. Lower $0.14/hr average cost makes it ideal for high-volume serving.
V100's superior 125 TFLOPS FP16 speeds fine-tuning iterations over RTX 4060 Ti's 15.1 TFLOPS. 900 GB/s bandwidth supports bigger batches.
RTX 4060 Ti's modern Ada architecture and 15.1 TFLOPS FP16 suffice for generation tasks at $0.14/hr. Lower TDP of 115W fits bursty workloads.
V100's 900 GB/s bandwidth and 16 GB HBM2 excel in simulations versus RTX 4060 Ti's 272 GB/s and 8 GB. FP16 at 125 TFLOPS boosts compute-heavy analysis.
Frequently Asked Questions
Which has more VRAM: RTX 4060 Ti or V100 16GB?▾
The V100 16GB provides 16 GB HBM2, doubling the RTX 4060 Ti's 8 GB GDDR6. This allows V100 to load larger models without swapping. Bandwidth also favors V100 at 900 GB/s over 272 GB/s.
Is RTX 4060 Ti cheaper than V100 in the cloud?▾
RTX 4060 Ti starts at $0.08/hr with $0.14/hr average across 6 offers, undercutting V100's $0.10/hr start and $0.82/hr average across 24 offers. This makes RTX 4060 Ti better for budget runs.
Which GPU is better for AI training?▾
V100 excels with 125 TFLOPS FP16 versus RTX 4060 Ti's 15.1 TFLOPS, ideal for mixed-precision training. Its 300W TDP supports sustained high loads.
What is the power consumption difference?▾
RTX 4060 Ti draws 115W TDP, far less than V100's 300W. This efficiency lowers cloud operational costs for RTX 4060 Ti in multi-instance setups.
Can RTX 4060 Ti replace V100 for inference?▾
Yes, with FP32 at 15.1 TFLOPS nearly matching V100's 15.7 TFLOPS. RTX 4060 Ti's lower $0.14/hr pricing suits scalable inference better.
What interconnects do they support?▾
V100 offers NVLink and PCIe 3.0 for multi-GPU scaling, while RTX 4060 Ti uses PCIe only. V100 suits clustered training; RTX 4060 Ti fits single-node tasks.
Which is cheaper to rent, the RTX 4060 or the V100?▾
Cloud rental prices for both the RTX 4060 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 4060 have compared to the V100?▾
The RTX 4060 has 8 GB of GDDR6 memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find RTX 4060 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 4060 and the V100?▾
The RTX 4060 uses the Ada Lovelace architecture (2023) while the V100 uses Volta (2017). The V100 delivers 8.3x the FP16 throughput and 3.3x the memory bandwidth of the RTX 4060.