Specifications Compared
| Spec | RTX-5060 | V100 |
|---|---|---|
| TDP | 180W | 300W |
| VRAM | 12 GB | 16-32 GB |
| CUDA Cores | 4,608 | 5,120 |
| Memory Type | GDDR7 | HBM2 |
| Architecture | Blackwell | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink, PCIe 3.0 | |
| Tensor Cores | 144 | 640 |
| FP16 Performance | 23.1 TFLOPS | 125 TFLOPS |
| FP32 Performance | 23.1 TFLOPS | 15.7 TFLOPS |
| INT8 Performance | 370 TOPS | |
| Memory Bandwidth | 448 GB/s | 900 GB/s |
Performance Analysis
V100 dominates FP16 workloads at 125 TFLOPS, enabling rapid matrix multiplications in deep learning training that outpace RTX 5060 Ti's 23.1 TFLOPS by over fivefold. This advantage pairs with 900 GB/s bandwidth, allowing larger batch sizes in training and inference without memory stalls, unlike the RTX 5060 Ti's 448 GB/s limit. Higher 16 GB VRAM on V100 further supports extensive datasets.
RTX 5060 Ti counters in FP32 scenarios with 23.1 TFLOPS exceeding V100's 15.7 TFLOPS, benefiting general-purpose computing or simulations. Lower 180W TDP versus 300W promotes efficiency in dense cloud clusters, while Blackwell architecture optimizes for contemporary software stacks. Bandwidth disparity impacts high-throughput inference: V100 sustains bigger models, but RTX 5060 Ti suffices for optimized inference at lower costs.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 5060 Ti
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA GeForce RTX 5060 Ti 16GB VRAM | 16GB | 128 vCPU 31GB RAM 673GB Storage | Maryland | $0.27/GPU/hr | Available | ||
Vast.ai | NVIDIA GeForce RTX 5060 Ti 16GB VRAM | 16GB | 128 vCPU 31GB RAM 1526GB Storage | Maryland | $0.27/GPU/hr | Available |
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 5060 Ti
Select RTX 5060 Ti for cost-driven deployments: rates average $0.15 per hour across 10 offers. It excels in inference tasks leveraging 23.1 TFLOPS FP32 and Blackwell optimizations for modern frameworks, alongside 180W TDP for power-efficient scaling. Gaming or lighter ML suits its PCIe form factor perfectly.
Budget users prioritizing new architecture support choose it over V100's higher $0.82 per hour average.
When to Choose the Tesla V100 16GB
Opt for V100 16GB in FP16-intensive training: 125 TFLOPS and 900 GB/s bandwidth handle large-scale models with 16 GB VRAM effectively. Legacy Volta codebases or NVLink-dependent multi-GPU setups favor its SXM2 form factor.
High-bandwidth needs like batch-heavy workloads justify $0.82 per hour average despite age.
Use Cases
V100 16GB delivers 125 TFLOPS FP16 for faster training epochs. Its 900 GB/s bandwidth manages large LLM batches superior to RTX 5060 Ti's 448 GB/s.
RTX 5060 Ti provides cost efficiency at $0.15 per hour average. Balanced 23.1 TFLOPS FP16/FP32 suits optimized inference on newer models.
RTX 5060 Ti works for small datasets with 12 GB VRAM at low $0.07 per hour starts. V100 16GB handles larger ones via 125 TFLOPS FP16.
RTX 5060 Ti leverages Blackwell for image gen at 23.1 TFLOPS FP16. Lower 180W TDP and $0.15 per hour average beat V100 costs.
RTX 5060 Ti leads FP32 at 23.1 TFLOPS over V100's 15.7 TFLOPS. Efficient 448 GB/s bandwidth supports simulations affordably.
Frequently Asked Questions
Which GPU has higher FP16 performance?▾
V100 16GB achieves 125 TFLOPS FP16, far exceeding RTX 5060 Ti's 23.1 TFLOPS. This suits tensor-heavy ML training. RTX 5060 Ti balances with equal FP32 at 23.1 TFLOPS.
What are the cloud pricing differences?▾
RTX 5060 Ti starts at $0.07 per hour, averaging $0.15 per hour over 10 offers. V100 16GB begins at $0.10 per hour, averaging $0.82 per hour across 26 offers. RTX offers better value for most tasks.
Does V100 have more VRAM?▾
V100 16GB provides 16 GB HBM2 versus RTX 5060 Ti's 12 GB GDDR7. Higher bandwidth at 900 GB/s enhances V100 data throughput. RTX suffices for smaller models.
Which is more power efficient?▾
RTX 5060 Ti consumes 180W TDP, half of V100's 300W. This enables denser cloud deployments. Blackwell architecture amplifies per-watt performance.
Is RTX 5060 Ti better for modern AI?▾
RTX 5060 Ti uses 2025 Blackwell architecture for current frameworks. It matches FP32 at 23.1 TFLOPS over V100's 15.7 TFLOPS. Lower costs seal its edge.
Can V100 use NVLink?▾
V100 supports NVLink interconnect for multi-GPU scaling. RTX 5060 Ti lacks it, relying on PCIe. V100 excels in legacy HPC clusters.
Which is cheaper to rent, the RTX 5060 or the V100?▾
Cloud rental prices for both the RTX 5060 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 5060 have compared to the V100?▾
The RTX 5060 has 12 GB of GDDR7 memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find RTX 5060 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 5060 and the V100?▾
The RTX 5060 uses the Blackwell architecture (2025) while the V100 uses Volta (2017). The V100 delivers 5.4x the FP16 throughput and 2.0x the memory bandwidth of the RTX 5060.