Specifications Compared
| Spec | RTX-4080 | V100 |
|---|---|---|
| TDP | 320W | 300W |
| VRAM | 16 GB | 16-32 GB |
| CUDA Cores | 9,728 | 5,120 |
| Memory Type | GDDR6X | HBM2 |
| Architecture | Ada Lovelace | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink, PCIe 3.0 | |
| Tensor Cores | 304 | 640 |
| FP16 Performance | 48.7 TFLOPS | 125 TFLOPS |
| FP32 Performance | 48.7 TFLOPS | 15.7 TFLOPS |
| INT8 Performance | 780 TOPS | |
| Memory Bandwidth | 717 GB/s | 900 GB/s |
Performance Analysis
The V100 holds a clear advantage in FP16 performance at 125 TFLOPS, doubling the RTX 4080's 48.7 TFLOPS, which benefits mixed-precision training where tensor core utilization peaks. However, the RTX 4080 dominates FP32 workloads with 48.7 TFLOPS against the V100's 15.7 TFLOPS, making it superior for inference tasks or simulations reliant on single-precision compute. These deltas translate to faster convergence in FP32-heavy training on the RTX 4080 and higher throughput in FP16-dominated deep learning on the V100.
Memory bandwidth favors the V100 at 900 GB/s over 717 GB/s, enabling larger batch sizes in memory-bound workloads like large language model training without swapping. The RTX 4080's slightly higher TDP of 320W compared to 300W suggests marginally greater power draw, but its newer architecture yields better real-world efficiency per watt. Overall, the V100 excels in bandwidth-intensive HPC, while the RTX 4080 balances compute for diverse AI pipelines.
Interconnect options further differentiate them: V100's NVLink supports multi-GPU scaling superior to the RTX 4080's PCIe, impacting distributed training speed.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 4080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4080 SUPER 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr | |||
RunPod | NVIDIA GeForce RTX 4080 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/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 4080
Opt for the RTX 4080 in modern inference and fine-tuning workflows requiring strong FP32 performance of 48.7 TFLOPS. Its lower average cloud pricing of $0.26 per hour across 5 offers makes it economical for single-GPU tasks like Stable Diffusion or real-time AI serving. The Ada Lovelace architecture ensures compatibility with the latest CUDA versions and frameworks.
Choose RTX 4080 for consumer-grade applications or when PCIe form factor simplifies deployment in versatile cloud instances.
When to Choose the Tesla V100 16GB
Select the V100 16GB for legacy Volta-optimized codebases leveraging its 125 TFLOPS FP16 and 900 GB/s HBM2 bandwidth. NVLink interconnect excels in multi-GPU training setups, outperforming PCIe-only scaling on RTX 4080. Despite higher average pricing of $0.82 per hour across 27 offers, it suits high-batch scientific computing.
The V100 fits datacenter environments with SXM2 support and established HPC pipelines from 2017.
Use Cases
V100's 125 TFLOPS FP16 and 900 GB/s bandwidth support larger batches in mixed-precision training. NVLink aids multi-GPU scaling for large models.
RTX 4080's 48.7 TFLOPS FP32 handles inference efficiently with lower latency. Its $0.26 per hour average cost suits cost-sensitive serving.
RTX 4080 matches FP16 and FP32 at 48.7 TFLOPS for balanced fine-tuning workloads. Newer architecture optimizes recent optimizers.
RTX 4080's Ada Lovelace excels in generative tasks with 48.7 TFLOPS compute and 16 GB GDDR6X. Lower TDP of 320W aids prolonged rendering.
V100's 900 GB/s HBM2 and NVLink suit memory-intensive simulations. 125 TFLOPS FP16 accelerates HPC kernels.
Frequently Asked Questions
Which GPU has higher FP16 performance?▾
The V100 achieves 125 TFLOPS in FP16, surpassing the RTX 4080's 48.7 TFLOPS. This makes V100 preferable for tensor core-heavy training. RTX 4080 balances with equal FP32 capability.
What are the memory bandwidth differences?▾
V100 offers 900 GB/s with HBM2, exceeding RTX 4080's 717 GB/s GDDR6X. Higher bandwidth on V100 supports larger batch sizes. Both have 16 GB VRAM.
How do cloud prices compare?▾
RTX 4080 starts at $0.11 per hour with $0.26 average across 5 offers, while V100 16GB starts at $0.10 per hour but averages $0.82 across 27 offers. RTX 4080 provides better value on average.
Which has better FP32 performance?▾
RTX 4080 delivers 48.7 TFLOPS FP32, triple the V100's 15.7 TFLOPS. This favors RTX 4080 for single-precision tasks like inference. V100 prioritizes FP16.
What interconnects do they support?▾
V100 includes NVLink and PCIe 3.0 for multi-GPU, while RTX 4080 uses PCIe only. NVLink on V100 enhances scaling. Form factors differ: SXM2/PCIe for V100, PCIe for RTX 4080.
Which is more power efficient?▾
V100 has lower TDP at 300W versus RTX 4080's 320W. However, Ada Lovelace architecture improves RTX 4080's efficiency per TFLOP. Choice depends on workload density.
Which is cheaper to rent, the RTX 4080 or the V100?▾
Cloud rental prices for both the RTX 4080 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 4080 have compared to the V100?▾
The RTX 4080 has 16 GB of GDDR6X memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find RTX 4080 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 4080 and the V100?▾
The RTX 4080 uses the Ada Lovelace architecture (2022) while the V100 uses Volta (2017). The V100 delivers 2.6x the FP16 throughput and 1.3x the memory bandwidth of the RTX 4080.