Specifications Compared
| Spec | RTX-3080 | V100 |
|---|---|---|
| TDP | 320W | 300W |
| VRAM | 10-12 GB | 16-32 GB |
| CUDA Cores | 8,704 | 5,120 |
| Memory Type | GDDR6X | HBM2 |
| Architecture | Ampere | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink, PCIe 3.0 | |
| Tensor Cores | 272 | 640 |
| FP16 Performance | 29.8 TFLOPS | 125 TFLOPS |
| FP32 Performance | 29.8 TFLOPS | 15.7 TFLOPS |
| Memory Bandwidth | 760 GB/s | 900 GB/s |
Performance Analysis
Memory specifications impact workload feasibility directly: the V100 16GB's 900 GB/s bandwidth and 16 GB HBM2 capacity support larger batch sizes in memory-intensive tasks than the RTX 3080 Ti's 760 GB/s and 10 to 12 GB GDDR6X. This advantage aids training scenarios where data transfer rates limit throughput. HBM2's lower latency further benefits multi-GPU setups via NVLink on the V100.
Floating-point performance reveals specialization: V100 16GB's 125 TFLOPS FP16 suits mixed-precision training, accelerating convergence by up to four times over FP32-only methods on compatible frameworks. RTX 3080 Ti's equal 29.8 TFLOPS in FP16 and FP32 favors inference and FP32-dominant simulations, where V100's 15.7 TFLOPS FP32 lags. For inference, RTX 3080 Ti handles higher throughput in batch sizes fitting its VRAM, while V100 thrives in FP16-heavy deep learning training epochs.
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 3080 Ti
The RTX 3080 Ti suits cost-sensitive deployments: its cloud pricing begins at $0.08 per hour, averaging $0.14 per hour, far below V100 16GB's $0.82 per hour average. Newer Ampere architecture enhances efficiency in TensorRT-optimized inference and Stable Diffusion generation, leveraging 29.8 TFLOPS FP32 for real-time tasks. Select it for single-GPU inference or fine-tuning models under 10 GB VRAM.
When to Choose the Tesla V100 16GB
The V100 16GB excels in large-scale training: 125 TFLOPS FP16 accelerates mixed-precision workflows, and 900 GB/s bandwidth enables batch sizes exceeding RTX 3080 Ti limits. NVLink interconnect supports multi-GPU scaling unavailable on PCIe-only RTX 3080 Ti. Choose it for scientific computing or LLM training requiring 16 GB HBM2 and high FP16 throughput.
Use Cases
V100 16GB's 125 TFLOPS FP16 outperforms RTX 3080 Ti's 29.8 TFLOPS for mixed-precision training, while 900 GB/s bandwidth handles large batches.
RTX 3080 Ti's 29.8 TFLOPS FP32 matches FP16 for efficient inference, and lower $0.14 per hour average cost suits high-volume serving.
RTX 3080 Ti balances 29.8 TFLOPS across precisions for fine-tuning under 12 GB VRAM, with cheaper $0.08 per hour minimum pricing.
Ampere architecture optimizes Stable Diffusion via 29.8 TFLOPS FP32 and 760 GB/s bandwidth for fast image generation.
V100 16GB's 16 GB HBM2 and NVLink enable multi-GPU simulations, surpassing RTX 3080 Ti in FP16-heavy HPC workloads.
Frequently Asked Questions
Which GPU has higher FP16 performance?▾
The V100 16GB delivers 125 TFLOPS FP16, far exceeding the RTX 3080 Ti's 29.8 TFLOPS. This makes V100 preferable for FP16-dominant training tasks.
What are the cloud pricing differences?▾
RTX 3080 Ti starts at $0.08 per hour, averaging $0.14 per hour across four offers. V100 16GB begins at $0.10 per hour, averaging $0.82 per hour across 27 offers.
Which has more VRAM?▾
V100 16GB provides 16 GB HBM2, compared to RTX 3080 Ti's 10 to 12 GB GDDR6X. V100 supports larger models directly.
Is RTX 3080 Ti better for inference?▾
RTX 3080 Ti's equal 29.8 TFLOPS FP16 and FP32 enables strong inference performance. Its lower cost enhances scalability for production serving.
Does V100 support multi-GPU better?▾
V100 16GB includes NVLink for high-bandwidth multi-GPU communication, unlike PCIe-only RTX 3080 Ti. This aids distributed training.
Which has higher memory bandwidth?▾
V100 16GB achieves 900 GB/s with HBM2, topping RTX 3080 Ti's 760 GB/s GDDR6X. Higher bandwidth reduces bottlenecks in data-heavy workloads.
Which is cheaper to rent, the RTX 3080 or the V100?▾
Cloud rental prices for both the RTX 3080 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 3080 have compared to the V100?▾
The RTX 3080 has 10 to 12 GB of GDDR6X memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find RTX 3080 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 3080 and the V100?▾
The RTX 3080 uses the Ampere architecture (2020) while the V100 uses Volta (2017). The V100 delivers 4.2x the FP16 throughput and 1.2x the memory bandwidth of the RTX 3080.