Specifications Compared
| Spec | A100 | RTX-4080 |
|---|---|---|
| TDP | 400W | 320W |
| VRAM | 40-80 GB | 16 GB |
| CUDA Cores | 6,912 | 9,728 |
| Memory Type | HBM2e | GDDR6X |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 304 |
| FP16 Performance | 312 TFLOPS | 48.7 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 48.7 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | 780 TOPS |
| Memory Bandwidth | 2,039 GB/s | 717 GB/s |
Performance Analysis
Key architectural differences define real-world capabilities: the A100 PCIe 80GB achieves 312 TFLOPS in FP16 for accelerated mixed-precision training, far exceeding the RTX 4080's 48.7 TFLOPS, while its FP32 performance of 19.5 TFLOPS trails the RTX 4080's balanced 48.7 TFLOPS. This FP16/FP32 delta means the A100 excels in deep learning training where half-precision computations dominate, enabling faster iterations on large neural networks, but the RTX 4080 handles general-purpose floating-point tasks more evenly.
Memory specifications profoundly impact workloads: the A100's 80 GB HBM2e VRAM and 2039 GB/s bandwidth accommodate enormous batch sizes in model training, reducing out-of-memory errors for datasets exceeding 16 GB, as limited by the RTX 4080. Lower bandwidth on the RTX 4080 at 717 GB/s constrains data throughput, slowing inference on memory-intensive tasks. Consequently, the A100 supports scalable multi-GPU setups via NVLink and PCIe 4.0, outperforming the RTX 4080's single PCIe form factor in distributed computing.
Power efficiency varies with TDP: the A100 consumes 400W for peak datacenter throughput, while the RTX 4080's 320W suits edge or cost-sensitive deployments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 PCIe 80GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 63GB RAM 397GB Storage | Slovenia | $0.73/GPU/hr | 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 | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 126GB RAM 1114GB Storage | Czechia | $1.00/GPU/hr $2.00/hr total (2×) | Available | ||
 Denvr | 4×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 512GB RAM 7600GB Storage | Virginia | $1.15/GPU/hr $4.60/hr total (4×) | |||
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 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 |
When to Choose the A100 PCIe 80GB
Select the NVIDIA A100 PCIe 80GB for enterprise-scale AI training and inference requiring over 16 GB VRAM: its 80 GB HBM2e capacity handles large language models without aggressive quantization. High memory bandwidth of 2039 GB/s enables massive batch sizes, accelerating convergence in distributed setups via NVLink and InfiniBand interconnects. Cloud pricing starts at $0.89 per hour across 28 offers, justified for production workloads demanding 312 TFLOPS FP16 performance.
When to Choose the RTX 4080
Opt for the NVIDIA GeForce RTX 4080 in budget-conscious scenarios like prototyping or inference on smaller models: its 16 GB GDDR6X VRAM suffices for tasks under that threshold at cloud rates from $0.11 per hour across 5 offers. Balanced 48.7 TFLOPS FP16 and FP32 performance supports graphics-intensive applications, with 320W TDP enabling efficient single-node use. Ada Lovelace optimizations benefit generative AI without the A100's overhead.
Use Cases
The A100 PCIe 80GB's 80 GB HBM2e VRAM and 312 TFLOPS FP16 performance support training massive language models with large batch sizes. The RTX 4080's 16 GB VRAM restricts model scale.
High 2039 GB/s bandwidth and 80 GB capacity on the A100 enable serving unquantized large models at scale. RTX 4080 suits smaller models but falters on memory-intensive inference.
RTX 4080 handles fine-tuning of models under 16 GB at low cost from $0.11 per hour. A100 excels for larger parameter counts needing 80 GB VRAM.
Ada Lovelace architecture on RTX 4080 optimizes generative tasks like Stable Diffusion with 48.7 TFLOPS and affordable $0.26 average hourly rate. A100 overkill for typical image generation.
A100's 2039 GB/s bandwidth and NVLink interconnect accelerate simulations with high data movement. RTX 4080's 717 GB/s limits complex scientific workloads.
Frequently Asked Questions
What is the VRAM capacity of the NVIDIA A100 PCIe 80GB versus RTX 4080?▾
The A100 PCIe 80GB provides 80 GB HBM2e VRAM, compared to the RTX 4080's 16 GB GDDR6X. This fivefold difference allows the A100 to manage larger datasets and models without memory constraints.
Which GPU has higher memory bandwidth?▾
The A100 PCIe 80GB delivers 2039 GB/s bandwidth, nearly three times the RTX 4080's 717 GB/s. Superior bandwidth enhances batch processing and data-intensive computations on the A100.
What are the cloud pricing differences?▾
RTX 4080 pricing starts at $0.11 per hour with an average of $0.26 across 5 offers, while A100 PCIe 80GB begins at $0.89 per hour averaging $2.08 across 28 offers. Cost favors RTX 4080 for light workloads.
Which is better for AI training FP16 performance?▾
A100 PCIe 80GB offers 312 TFLOPS in FP16, surpassing RTX 4080's 48.7 TFLOPS by over six times. This makes A100 ideal for mixed-precision training of deep networks.
How do power consumptions compare?▾
The A100 PCIe 80GB has a 400W TDP, higher than the RTX 4080's 320W. Lower TDP on RTX 4080 reduces cooling needs in smaller deployments.
What interconnects does each support?▾
A100 PCIe 80GB includes NVLink, PCIe 4.0, and InfiniBand for multi-GPU scaling. RTX 4080 relies solely on PCIe, limiting distributed performance.
Which is cheaper to rent, the A100 or the RTX 4080?▾
Cloud rental prices for both the A100 and RTX 4080 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 4080?▾
The A100 has 40 to 80 GB of HBM2e memory. The RTX 4080 has 16 GB of GDDR6X memory.
Can I find A100 and RTX 4080 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 4080?▾
The A100 uses the Ampere architecture (2020) while the RTX 4080 uses Ada Lovelace (2022). The A100 delivers 6.4x the FP16 throughput and 2.8x the memory bandwidth of the RTX 4080.