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's FP16 performance of 125 TFLOPS vastly exceeds the RTX 4060's 15.1 TFLOPS, providing substantial acceleration for training deep learning models using mixed-precision arithmetic, which reduces memory usage while maintaining accuracy. In contrast, FP32 rates align closely at 15.7 TFLOPS for V100 and 15.1 TFLOPS for RTX 4060, implying similar throughput for inference tasks or simulations reliant on single-precision floating point.
Memory bandwidth represents a critical disparity: V100's 900 GB/s enables handling larger batch sizes in training without bottlenecks, unlike the RTX 4060's 272 GB/s which limits scalability for data-intensive workloads. The V100's 16-32 GB HBM2 VRAM supports loading extensive models or datasets entirely in memory, avoiding slowdowns from the RTX 4060's 8 GB GDDR6 constraint. Power consumption also differs markedly, with V100 at 300W TDP versus RTX 4060's efficient 115W, influencing deployment density in cloud clusters.
These specs translate to real-world trade-offs: V100 prioritizes raw throughput for heavy AI training, while RTX 4060 offers cost-effective viability for lighter or power-sensitive applications.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
V100
| 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
The RTX 4060 proves superior for cost-sensitive projects requiring modest compute. Its pricing from $0.08/hr averaging $0.14/hr across 10 offers undercuts the V100's $0.94/hr average, enabling extended runtime on tight budgets. The 115W TDP facilitates higher instance density in cloud environments compared to V100's 300W draw.
Select RTX 4060 for inference-heavy workloads or development testing where 15.1 TFLOPS FP32 suffices and 8 GB VRAM handles smaller models, leveraging the newer Ada Lovelace architecture for optimized software compatibility.
When to Choose the V100
The V100 stands out for demanding training scenarios needing peak FP16 performance. Its 125 TFLOPS in FP16 accelerates model convergence far beyond RTX 4060's 15.1 TFLOPS, ideal for large-scale deep learning.
Choose V100 when memory constraints bind: 16-32 GB HBM2 and 900 GB/s bandwidth support massive batch sizes and complex models, unavailable on RTX 4060's 8 GB GDDR6 at 272 GB/s. NVLink interconnect enhances multi-GPU scaling over RTX 4060's PCIe alone.
Use Cases
V100's 125 TFLOPS FP16 and 16-32 GB HBM2 handle massive parameter counts and large batches effectively. RTX 4060's 8 GB VRAM and 15.1 TFLOPS FP16 fall short for scale.
RTX 4060's 15.1 TFLOPS FP32 matches V100's 15.7 TFLOPS closely for single-precision serving, with lower $0.14/hr average cost suiting high-volume queries. V100's strengths in FP16 add little value here.
V100 excels with 900 GB/s bandwidth for gradient computations on adapted large models using its 16-32 GB VRAM. RTX 4060's 272 GB/s limits efficiency.
RTX 4060's Ada Lovelace architecture optimizes generative tasks at 15.1 TFLOPS with 8 GB VRAM sufficient for standard resolutions, at $0.08/hr starting price. V100's age reduces software efficiency.
V100's 125 TFLOPS FP16 accelerates simulations like molecular dynamics, paired with NVLink for multi-GPU precision work. RTX 4060 lacks comparable half-precision scale.
Frequently Asked Questions
Which has more VRAM: RTX 4060 or V100?▾
The V100 provides 16-32 GB HBM2, doubling or quadrupling the RTX 4060's 8 GB GDDR6. This enables V100 to load larger models without out-of-memory errors in training.
Is RTX 4060 cheaper than V100 in the cloud?▾
RTX 4060 starts at $0.08/hr with $0.14/hr average across 10 offers, versus V100's $0.10/hr start and $0.94/hr average over 72 offers. RTX 4060 suits budget runs.
What is the FP16 performance difference?▾
V100 delivers 125 TFLOPS FP16, over eight times the RTX 4060's 15.1 TFLOPS. This gap favors V100 for mixed-precision training acceleration.
Which GPU uses less power?▾
RTX 4060 consumes 115W TDP, less than half of V100's 300W. Lower power supports denser cloud deployments for RTX 4060.
Does V100 support NVLink?▾
V100 includes NVLink alongside PCIe 3.0 for high-speed multi-GPU communication, absent on RTX 4060's PCIe form factor. This boosts scaled training.
How do memory bandwidths compare?▾
V100 offers 900 GB/s, over three times the RTX 4060's 272 GB/s. Higher bandwidth on V100 reduces bottlenecks in large-batch processing.
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.