Specifications Compared
| Spec | A100 | RTX-3080 |
|---|---|---|
| TDP | 400W | 320W |
| VRAM | 40-80 GB | 10-12 GB |
| CUDA Cores | 6,912 | 8,704 |
| Memory Type | HBM2e | GDDR6X |
| Architecture | Ampere | Ampere |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 272 |
| FP16 Performance | 312 TFLOPS | 29.8 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 29.8 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | |
| Memory Bandwidth | 2,039 GB/s | 760 GB/s |
Performance Analysis
FP16 performance defines training advantages: the A100 achieves 312 TFLOPS, over 10 times the RTX 3080's 29.8 TFLOPS, accelerating deep learning forward passes. FP32 parity shifts with the RTX 3080 at 29.8 TFLOPS exceeding the A100's 19.5 TFLOPS, benefiting simulation or graphics tasks.
Memory specs impact real-world usage profoundly. The A100's 40 to 80 GB HBM2e and 2039 GB/s bandwidth support massive batch sizes in model training, fitting large language models without swapping. The RTX 3080's 10 to 12 GB GDDR6X at 760 GB/s limits batches, causing out-of-memory errors for datasets over 10 GB.
Interconnects enhance scalability: the A100 uses NVLink and PCIe 4.0 for multi-GPU clusters, while the RTX 3080 relies solely on PCIe. Higher TDP of 400W on the A100 demands robust cooling, yet yields throughput gains in sustained 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×) |
When to Choose the A100
The A100 suits enterprise-scale AI training and inference. Its 40 to 80 GB VRAM handles models exceeding 12 GB, such as large LLMs, without quantization. NVLink interconnect enables efficient multi-GPU setups for distributed training.
High memory bandwidth of 2039 GB/s supports large batch sizes, reducing training time in scientific computing workloads.
When to Choose the RTX 3080
The RTX 3080 fits budget-conscious users for prototyping or gaming-integrated ML. At $0.06 per hour average $0.15, it undercuts A100 pricing by over 10 times, ideal for small teams.
Its 29.8 TFLOPS FP32 outperforms the A100's 19.5 TFLOPS for rendering or simulations, with 10 to 12 GB VRAM sufficient for fine-tuning models under 10 GB.
Use Cases
The A100's 312 TFLOPS FP16 and 40 to 80 GB VRAM manage large datasets and models. The RTX 3080's 10 to 12 GB VRAM causes memory constraints.
A100's 2039 GB/s bandwidth supports high-throughput serving of models over 12 GB. RTX 3080 suits only quantized small models.
RTX 3080 handles models under 10 GB cost-effectively at $0.06 per hour. A100 excels for larger parameter counts with 40 GB VRAM.
RTX 3080's 29.8 TFLOPS FP32 and gaming optimizations generate images quickly on 10 GB VRAM. A100 overkill for consumer diffusion tasks.
A100's 312 TFLOPS FP16 accelerates simulations with large data via 2039 GB/s bandwidth. RTX 3080's lower specs limit complex computations.
Frequently Asked Questions
Is A100 better than RTX 3080 for AI training?▾
Yes, the A100's 312 TFLOPS FP16 dwarfs the RTX 3080's 29.8 TFLOPS, speeding training. Its 40 to 80 GB VRAM fits large models unlike 10 to 12 GB.
How much VRAM does A100 have compared to RTX 3080?▾
A100 offers 40 to 80 GB HBM2e, enabling bigger batches. RTX 3080 provides 10 to 12 GB GDDR6X, suitable for smaller workloads.
What is the price difference in cloud for A100 vs RTX 3080?▾
A100 starts at $0.45 per hour averaging $1.89 across 60 offers. RTX 3080 begins at $0.06 per hour averaging $0.15 across 10 offers.
RTX 3080 vs A100 memory bandwidth?▾
A100 delivers 2039 GB/s with HBM2e for high throughput. RTX 3080 achieves 760 GB/s with GDDR6X, adequate for consumer tasks.
Can RTX 3080 replace A100 for ML inference?▾
Only for models under 10 GB; RTX 3080's VRAM limits larger ones. A100's capacity and 312 TFLOPS FP16 ensure scalability.
Power consumption A100 vs RTX 3080?▾
A100 TDP is 400W for datacenter use. RTX 3080 draws 320W, easier for consumer setups.
Which is cheaper to rent, the A100 or the RTX 3080?▾
Cloud rental prices for both the A100 and RTX 3080 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 3080?▾
The A100 has 40 to 80 GB of HBM2e memory. The RTX 3080 has 10 to 12 GB of GDDR6X memory.
Can I find A100 and RTX 3080 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 3080?▾
The A100 uses the Ampere architecture (2020) while the RTX 3080 uses Ampere (2020). The A100 delivers 10.5x the FP16 throughput and 2.7x the memory bandwidth of the RTX 3080.