Specifications Compared
| Spec | A100 | RTX-5080 |
|---|---|---|
| TDP | 400W | 360W |
| VRAM | 40-80 GB | 16 GB |
| CUDA Cores | 6,912 | 10,752 |
| Memory Type | HBM2e | GDDR7 |
| Architecture | Ampere | Blackwell |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 336 |
| FP16 Performance | 312 TFLOPS | 56.3 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 56.3 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | 900 TOPS |
| Memory Bandwidth | 2,039 GB/s | 960 GB/s |
Performance Analysis
FP16 performance differentiates these GPUs sharply: the A100 achieves 312 TFLOPS, enabling faster training of deep learning models that leverage half-precision arithmetic, whereas the RTX 5080 delivers 56.3 TFLOPS, sufficient for inference but limiting throughput on large batches. In FP32, the RTX 5080 matches its FP16 at 56.3 TFLOPS, surpassing the A100's 19.5 TFLOPS for tasks like simulations requiring full single-precision accuracy.
Memory specifications impact real-world usage profoundly: A100's 80 GB HBM2e and 2039 GB/s bandwidth support massive models and large batch sizes without out-of-memory issues, accelerating convergence in training cycles. The RTX 5080's 16 GB GDDR7 at 960 GB/s handles smaller datasets efficiently but constrains scalability for memory-bound workloads. TDP ratings of 400W for A100 and 360W for RTX 5080 suggest comparable power draw per performance unit in cloud environments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 SXM4 80GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 63GB RAM 2826GB Storage | Slovenia | $0.73/GPU/hr | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 794GB Storage | Slovenia | $0.73/GPU/hr $1.47/hr total (2×) | Available | ||
 LeaderGPU | 8×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.90/GPU/hr $7.20/hr total (8×) | Available | ||
Vast.ai | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 63GB RAM 557GB Storage | Czechia | $1.00/GPU/hr | Available | ||
 Denvr | 8×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 128 vCPU 1024GB RAM 15200GB Storage | Virginia | $1.15/GPU/hr $9.20/hr total (8×) |
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 |
When to Choose the A100 SXM4 80GB
Select the A100 SXM4 80GB for memory-intensive applications like training large language models exceeding 16 GB VRAM requirements. Its 80 GB HBM2e capacity and 2039 GB/s bandwidth enable larger batch sizes, while NVLink and InfiniBand interconnects facilitate multi-GPU clusters for distributed training at scale.
When to Choose the RTX 5080
Opt for the RTX 5080 in budget-conscious scenarios with its average cloud price of $0.38/hr across offers. The Blackwell architecture and 56.3 TFLOPS FP32 performance suit inference, fine-tuning of compact models, and graphics tasks fitting within 16 GB GDDR7.
Use Cases
The A100's 80 GB VRAM and 312 TFLOPS FP16 support massive models and large batches critical for efficient training. RTX 5080's 16 GB restricts scalability.
RTX 5080's 56.3 TFLOPS FP16 and lower $0.38/hr average price enable cost-effective serving of models under 16 GB. A100 suits only high-throughput needs.
A100's 2039 GB/s bandwidth and 80 GB capacity manage parameter-efficient fine-tuning on large datasets without memory constraints. RTX 5080 fits smaller adapters.
RTX 5080's GDDR7 memory and Blackwell features optimize image generation pipelines within 16 GB limits at $0.38/hr average. A100 overprovisions for this.
RTX 5080's 56.3 TFLOPS FP32 outperforms A100's 19.5 TFLOPS for precision simulations. Lower TDP of 360W aids efficiency.
Frequently Asked Questions
Which GPU has more VRAM: A100 SXM4 80GB or RTX 5080?▾
The A100 SXM4 80GB provides 80 GB HBM2e VRAM, far exceeding the RTX 5080's 16 GB GDDR7. This makes A100 suitable for larger models. RTX 5080 suffices for compact workloads.
What are the cloud prices for these GPUs?▾
A100 SXM4 80GB starts at $0.13/hr with an average of $1.30/hr across 28 offers. RTX 5080 begins at $0.25/hr averaging $0.38/hr over 4 offers. Prices reflect availability on gpuperhour.com.
Which is better for AI training?▾
A100 excels with 312 TFLOPS FP16 and 80 GB VRAM for training large models. RTX 5080's 56.3 TFLOPS limits it to smaller scales. Bandwidth of 2039 GB/s on A100 boosts batch sizes.
How do memory bandwidths compare?▾
A100 offers 2039 GB/s, doubling RTX 5080's 960 GB/s. Higher bandwidth on A100 reduces bottlenecks in data-heavy tasks. This impacts training efficiency directly.
What are the TDP values?▾
A100 has a 400W TDP, while RTX 5080 uses 360W. Both suit cloud deployments with similar power profiles. Efficiency favors RTX 5080 slightly per watt in FP32.
Which architecture is newer?▾
RTX 5080 uses Blackwell from 2025, succeeding A100's Ampere of 2020. Newer architecture brings optimizations for RTX 5080. A100 retains datacenter advantages.
Which is cheaper to rent, the A100 or the RTX 5080?▾
Cloud rental prices for both the A100 and RTX 5080 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 A100 have compared to the RTX 5080?▾
The A100 has 40 to 80 GB of HBM2e memory. The RTX 5080 has 16 GB of GDDR7 memory.
Can I find A100 and RTX 5080 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 A100 and the RTX 5080?▾
The A100 uses the Ampere architecture (2020) while the RTX 5080 uses Blackwell (2025). The A100 delivers 5.5x the FP16 throughput and 2.1x the memory bandwidth of the RTX 5080.