Specifications Compared
| Spec | RTX-5080 | V100 |
|---|---|---|
| TDP | 360W | 300W |
| VRAM | 16 GB | 16-32 GB |
| CUDA Cores | 10,752 | 5,120 |
| Memory Type | GDDR7 | HBM2 |
| Architecture | Blackwell | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink, PCIe 3.0 | |
| Tensor Cores | 336 | 640 |
| FP16 Performance | 56.3 TFLOPS | 125 TFLOPS |
| FP32 Performance | 56.3 TFLOPS | 15.7 TFLOPS |
| INT8 Performance | 900 TOPS | |
| Memory Bandwidth | 960 GB/s | 900 GB/s |
Performance Analysis
The FP16 performance disparity defines key workloads: the V100's 125 TFLOPS excels in half-precision inference and training, enabling faster throughput for large language models in FP16 mode compared to the RTX 5080's 56.3 TFLOPS. However, the RTX 5080's equal 56.3 TFLOPS in FP32 outperforms the V100's 15.7 TFLOPS, benefiting single-precision tasks like scientific simulations or fine-tuning where full precision maintains accuracy.
Memory bandwidth impacts batch sizes directly: the RTX 5080's 960 GB/s supports larger batches in memory-bound inference than the V100's 900 GB/s, reducing latency in modern frameworks optimized for Blackwell. The RTX 5080's PCIe form factor limits multi-GPU scaling without NVLink, unlike the V100's NVLink and PCIe 3.0 support, which aids distributed training. Newer architecture ensures better software compatibility and efficiency for contemporary AI pipelines.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 5080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 5080 16GB VRAM | 16GB | 0 vCPU 0GB RAM | 🌍global | $0.59/GPU/hr |
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 5080
Choose the RTX 5080 for balanced compute in FP32-heavy workloads such as fine-tuning or scientific computing, where its 56.3 TFLOPS surpasses the V100's 15.7 TFLOPS. Its 2025 Blackwell architecture integrates seamlessly with latest CUDA versions and TensorRT, ideal for developers prioritizing modern software support and slightly higher 960 GB/s bandwidth for efficient batch processing at an average cloud cost of $0.38 per hour.
When to Choose the Tesla V100 16GB
Select the V100 for FP16-dominant inference tasks, leveraging its 125 TFLOPS to achieve higher throughput than the RTX 5080's 56.3 TFLOPS in half-precision scenarios like LLM serving. Greater availability across 26 cloud offers starting at $0.10 per hour suits budget-conscious users, while NVLink enables superior multi-GPU scaling for distributed training absent in the RTX 5080's PCIe-only design.
Use Cases
The RTX 5080's 56.3 TFLOPS FP32 supports precise gradient computations essential for training, exceeding the V100's 15.7 TFLOPS. Its modern Blackwell architecture optimizes for current frameworks.
The V100's 125 TFLOPS FP16 delivers superior half-precision throughput for serving large models. Lower starting price of $0.10 per hour enhances cost efficiency.
Balanced 56.3 TFLOPS FP32/FP16 on RTX 5080 handles mixed-precision fine-tuning better than V100's FP32 deficit at 15.7 TFLOPS. Newer GDDR7 memory aids smaller batch iterations.
RTX 5080's Blackwell architecture and 56.3 TFLOPS FP16 accelerate generative tasks with optimized RT cores. Higher 960 GB/s bandwidth supports larger image resolutions.
RTX 5080's 56.3 TFLOPS FP32 outperforms V100's 15.7 TFLOPS for simulations requiring full precision. PCIe form factor suffices for single-node cloud workloads.
Frequently Asked Questions
Which GPU has higher FP16 performance?▾
The V100 leads with 125 TFLOPS FP16 compared to the RTX 5080's 56.3 TFLOPS. This advantage suits half-precision inference tasks. FP32 performance reverses, with RTX 5080 at 56.3 TFLOPS versus V100's 15.7 TFLOPS.
How do memory bandwidths compare?▾
RTX 5080 offers 960 GB/s with GDDR7, slightly exceeding V100's 900 GB/s HBM2. Higher bandwidth on RTX 5080 enables larger batch sizes in memory-bound workloads. Both have 16 GB VRAM for similar model capacities.
What are the cloud pricing differences?▾
V100 starts at $0.10 per hour (average $0.82 per hour across 26 offers), cheaper entry than RTX 5080's $0.25 per hour (average $0.38 per hour across 4 offers). V100 provides more availability options. RTX 5080 offers better average value for modern tasks.
Which has lower power consumption?▾
V100 consumes 300 W TDP, lower than RTX 5080's 360 W. This benefits dense cloud deployments. Performance per watt favors RTX 5080 in balanced FP32 workloads at 56.3 TFLOPS.
Does V100 support multi-GPU better?▾
V100 includes NVLink and PCIe 3.0 for superior interconnect scaling over RTX 5080's PCIe-only design. This excels in distributed training. RTX 5080 suffices for single-GPU cloud instances.
Which is newer architecture?▾
RTX 5080 uses 2025 Blackwell architecture, far newer than V100's 2017 Volta. Blackwell ensures compatibility with latest AI libraries. V100 remains viable for legacy FP16-heavy codes.
Which is cheaper to rent, the RTX 5080 or the V100?▾
Cloud rental prices for both the RTX 5080 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 5080 have compared to the V100?▾
The RTX 5080 has 16 GB of GDDR7 memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find RTX 5080 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 5080 and the V100?▾
The RTX 5080 uses the Blackwell architecture (2025) while the V100 uses Volta (2017). The V100 delivers 2.2x the FP16 throughput and 1.1x the memory bandwidth of the RTX 5080.