Specifications Compared
| Spec | A100 | GTX-1080 |
|---|---|---|
| TDP | 400W | 180W |
| VRAM | 40-80 GB | 8-11 GB |
| CUDA Cores | 6,912 | 2,560 |
| Memory Type | HBM2e | GDDR5X |
| Architecture | Ampere | Pascal |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | |
| FP16 Performance | 312 TFLOPS | 8.9 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 8.9 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | |
| Memory Bandwidth | 2,039 GB/s | 320 GB/s |
Performance Analysis
The A100's FP16 performance of 312 TFLOPS dwarfs the GTX 1080's 8.9 TFLOPS, enabling up to 35 times faster half-precision computations critical for deep learning training and inference. This delta accelerates model training epochs and supports larger batch sizes without precision loss. FP32 performance on the A100 reaches 19.5 TFLOPS versus 8.9 TFLOPS on the GTX 1080, benefiting scientific simulations and single-precision tasks by more than double.
Memory bandwidth defines real-world throughput: the A100's 2039 GB/s versus 320 GB/s on the GTX 1080 permits batch sizes 6 times larger, reducing overhead in memory-bound workloads like transformer models. Lower bandwidth on the GTX 1080 limits it to smaller models or lower resolutions, causing out-of-memory errors for datasets exceeding 8 to 11 GB VRAM. Power draw also differs: 400W TDP for A100 suits data centers, while 180W on GTX 1080 favors edge or low-cost setups.
These specs translate to the A100 completing AI training runs in hours that take days on GTX 1080, though the older card suffices for non-demanding inference.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100
| 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 646GB Storage | Czechia | $1.07/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×) |
GTX 1080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
LeaderGPU | 4×NVIDIA GeForce GTX 1080 8GB VRAM | 8GB | 0 vCPU 64GB RAM 480GB Storage | Netherlands | $0.30/GPU/hr $1.20/hr total (4×) | Available | ||
LeaderGPU | 8×NVIDIA GeForce GTX 1080 Ti 11GB VRAM | 11GB | 0 vCPU 128GB RAM 480GB Storage | Netherlands | $0.60/GPU/hr $4.80/hr total (8×) | Available |
When to Choose the A100
Choose the A100 for large-scale LLM training or fine-tuning where 40 to 80 GB VRAM handles models with billions of parameters. Its 312 TFLOPS FP16 and 2039 GB/s bandwidth support massive batch sizes, reducing training time significantly compared to the GTX 1080's limitations. Professional workflows in cloud environments benefit from NVLink interconnects and PCIe 4.0 for multi-GPU scaling.
Scientific computing with high FP32 demands, at 19.5 TFLOPS, also favors the A100 over the GTX 1080's 8.9 TFLOPS.
When to Choose the GTX 1080
Opt for the GTX 1080 in budget-constrained prototyping or lightweight inference tasks fitting within 8 to 11 GB VRAM. Its $0.30 per hour starting price, averaging $0.45, makes it ideal for hobbyists or small-scale Stable Diffusion runs at lower resolutions. The 180W TDP enables deployment on consumer hardware without high power costs.
Gaming or legacy CUDA applications not requiring HBM2e bandwidth see no need for the A100's premium features.
Use Cases
The A100's 40-80 GB VRAM and 312 TFLOPS FP16 handle large language models without memory constraints. GTX 1080's 8-11 GB limits it to tiny batches or toy models.
A100's 2039 GB/s bandwidth supports high-throughput serving of billion-parameter models. GTX 1080 suffices only for small models under 8 GB.
Fine-tuning demands 19.5 TFLOPS FP32 and ample VRAM on A100 for efficient gradient computations. GTX 1080's 8.9 TFLOPS slows iterations significantly.
GTX 1080 runs basic image generation at 8-11 GB VRAM for quick tests. A100 excels in high-resolution or batched Stable Diffusion with 40-80 GB capacity.
A100's 2039 GB/s bandwidth and 19.5 TFLOPS FP32 accelerate simulations. GTX 1080's 320 GB/s bottlenecks complex datasets.
Frequently Asked Questions
What is the VRAM difference between A100 and GTX 1080?▾
The A100 provides 40 to 80 GB HBM2e VRAM, enabling large models. GTX 1080 offers 8 to 11 GB GDDR5X, suitable for smaller workloads. This 5 to 10 times gap affects batch sizes in training.
How do FP16 performances compare?▾
A100 delivers 312 TFLOPS FP16 for rapid AI training. GTX 1080 achieves 8.9 TFLOPS, about 35 times slower. This impacts deep learning speed significantly.
Which has higher memory bandwidth?▾
A100's 2039 GB/s far exceeds GTX 1080's 320 GB/s by over six times. Higher bandwidth on A100 supports larger data transfers in ML pipelines.
What are the cloud pricing differences?▾
A100 starts at $0.45 per hour, averaging $1.92 across 57 offers. GTX 1080 starts at $0.30 per hour, averaging $0.45 across 2 offers. Budget tasks favor GTX 1080.
Is GTX 1080 viable for machine learning?▾
GTX 1080 works for prototyping with 8.9 TFLOPS FP32 and 180W TDP. It struggles with models over 8 GB VRAM, unlike A100's capabilities.
When was each GPU released?▾
A100 launched in 2020 with Ampere architecture for data centers. GTX 1080 came in 2016 via Pascal for gaming. The four-year gap explains spec disparities.
Which is cheaper to rent, the A100 or the GTX 1080?▾
Cloud rental prices for both the A100 and GTX 1080 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 GTX 1080?▾
The A100 has 40 to 80 GB of HBM2e memory. The GTX 1080 has 8 to 11 GB of GDDR5X memory.
Can I find A100 and GTX 1080 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 GTX 1080?▾
The A100 uses the Ampere architecture (2020) while the GTX 1080 uses Pascal (2016). The A100 delivers 35.1x the FP16 throughput and 6.4x the memory bandwidth of the GTX 1080.