Specifications Compared
| Spec | RTX-5070 | V100 |
|---|---|---|
| TDP | 250W | 300W |
| VRAM | 12 GB | 16-32 GB |
| CUDA Cores | 6,144 | 5,120 |
| Memory Type | GDDR7 | HBM2 |
| Architecture | Blackwell | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink, PCIe 3.0 | |
| Tensor Cores | 192 | 640 |
| FP16 Performance | 40.6 TFLOPS | 125 TFLOPS |
| FP32 Performance | 40.6 TFLOPS | 15.7 TFLOPS |
| INT8 Performance | 650 TOPS | |
| Memory Bandwidth | 448 GB/s | 900 GB/s |
Performance Analysis
The V100 16GB dominates FP16 performance at 125 TFLOPS, tripling the RTX 5070 Ti's 40.6 TFLOPS: this accelerates mixed-precision training for large models where half-precision computations reduce memory use without much accuracy loss. Inference workloads benefit similarly, as high FP16 throughput handles batched predictions efficiently on the V100 16GB. Conversely, the RTX 5070 Ti's 40.6 TFLOPS FP32 surpasses the V100 16GB's 15.7 TFLOPS, suiting single-precision tasks like certain simulations or graphics rendering. Memory bandwidth underscores this divide: the V100 16GB's 900 GB/s supports larger batch sizes in training, minimizing data starvation for models exceeding 12 GB VRAM limits, while the RTX 5070 Ti's 448 GB/s constrains it to smaller batches. The V100 16GB's HBM2 also edges out GDDR7 in latency-sensitive HPC. Overall, the V100 16GB excels in throughput-heavy AI pipelines, but the RTX 5070 Ti offers balanced compute at lower 250W TDP versus 300W.
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 5070 Ti
The RTX 5070 Ti suits inference-heavy or FP32-dominant workloads like real-time image processing, where its 40.6 TFLOPS FP32 outperforms the V100 16GB's 15.7 TFLOPS. Lower average cloud pricing at $0.19 per hour and 250W TDP make it ideal for cost-conscious, power-limited setups. Newer Blackwell architecture provides modern features like improved ray tracing for hybrid creative tasks.
When to Choose the Tesla V100 16GB
Opt for the V100 16GB in FP16-intensive training scenarios, leveraging 125 TFLOPS and 900 GB/s bandwidth for large-batch deep learning. Its 16 GB HBM2 VRAM and NVLink interconnect enable multi-GPU scaling unavailable on the PCIe-only RTX 5070 Ti. Datacenter pedigree ensures reliability for sustained HPC runs.
Use Cases
The V100 16GB's 125 TFLOPS FP16 and 900 GB/s bandwidth handle large-scale LLM training with bigger batches than the RTX 5070 Ti's 40.6 TFLOPS and 448 GB/s.
RTX 5070 Ti's balanced 40.6 TFLOPS FP16/FP32 fits low-latency inference, while V100 16GB's 125 TFLOPS FP16 excels in high-throughput serving. Choice depends on batch size needs.
V100 16GB's 16 GB VRAM and 125 TFLOPS FP16 support fine-tuning larger models without OOM errors, outperforming RTX 5070 Ti's 12 GB limit.
RTX 5070 Ti's 40.6 TFLOPS FP32 and modern Blackwell architecture accelerate diffusion model generation faster than V100 16GB's 15.7 TFLOPS FP32.
RTX 5070 Ti's superior 40.6 TFLOPS FP32 handles simulations better than V100 16GB's 15.7 TFLOPS, with lower 250W TDP for extended runs.
Frequently Asked Questions
Which GPU has more VRAM?▾
The V100 16GB provides 16 GB HBM2, exceeding the RTX 5070 Ti's 12 GB GDDR7. This allows larger models on the V100 16GB. Bandwidth follows suit at 900 GB/s versus 448 GB/s.
What is the FP16 performance difference?▾
V100 16GB achieves 125 TFLOPS FP16, over three times the RTX 5070 Ti's 40.6 TFLOPS. This gap favors V100 16GB for mixed-precision AI training. FP32 reverses: 40.6 TFLOPS on RTX 5070 Ti beats 15.7 TFLOPS.
How do cloud prices compare?▾
Both start at $0.10 per hour, but RTX 5070 Ti averages $0.19 per hour over two offers while V100 16GB averages $0.82 per hour over 26 offers. RTX 5070 Ti wins on cost efficiency.
Which has higher power consumption?▾
V100 16GB draws 300W TDP compared to RTX 5070 Ti's 250W. Lower TDP on RTX 5070 Ti suits dense cloud deployments. Form factors differ: SXM2/PCIe for V100 16GB, PCIe for RTX 5070 Ti.
Is the RTX 5070 Ti newer than V100 16GB?▾
RTX 5070 Ti uses 2025 Blackwell architecture, versus V100 16GB's 2017 Volta. Newer design brings efficiency gains at 250W. V100 16GB retains NVLink for multi-GPU.
Which supports better multi-GPU scaling?▾
V100 16GB includes NVLink and PCIe 3.0, enabling high-speed multi-GPU setups. RTX 5070 Ti relies on PCIe alone. This makes V100 16GB preferable for distributed training.
Which is cheaper to rent, the RTX 5070 or the V100?▾
Cloud rental prices for both the RTX 5070 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 5070 have compared to the V100?▾
The RTX 5070 has 12 GB of GDDR7 memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find RTX 5070 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 5070 and the V100?▾
The RTX 5070 uses the Blackwell architecture (2025) while the V100 uses Volta (2017). The V100 delivers 3.1x the FP16 throughput and 2.0x the memory bandwidth of the RTX 5070.