Specifications Compared
| Spec | A100 | GTX-1070 |
|---|---|---|
| TDP | 400W | 150W |
| VRAM | 40-80 GB | 8 GB |
| CUDA Cores | 6,912 | 1,920 |
| Memory Type | HBM2e | GDDR5 |
| Architecture | Ampere | Pascal |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | |
| FP16 Performance | 312 TFLOPS | 6.5 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 6.5 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | |
| Memory Bandwidth | 2,039 GB/s | 256 GB/s |
Performance Analysis
The A100 SXM4 80GB vastly outperforms the GTX 1070 Ti in FP16 compute: 312 TFLOPS versus 11.2 TFLOPS enables up to 28 times faster training and inference for deep learning models reliant on half-precision arithmetic. FP32 performance shows the A100 at 19.5 TFLOPS against 11.2 TFLOPS, a 74 percent advantage for general-purpose floating-point tasks. This delta means the A100 handles complex neural networks efficiently, while the 1070 Ti struggles with modern workloads. Memory capacity defines feasibility: 80 GB HBM2e on the A100 loads large language models intact, but 8 GB GDDR5 on the 1070 Ti forces model sharding or tiny batches. Bandwidth disparity amplifies this: 2039 GB/s versus 308 GB/s allows the A100 to sustain high throughput with large batch sizes, reducing data starvation in training loops. The 1070 Ti's lower 180W TDP suits power-constrained setups, yet its 400W counterpart in the A100 delivers proportional gains in datacenter 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 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 SXM4 80GB
Choose the A100 SXM4 80GB for demanding AI workloads requiring high VRAM and compute. Its 80 GB HBM2e supports training large models with batch sizes infeasible on 8 GB cards. Cloud access at $0.67 per hour average $1.39 enables scalable deployments across 26 providers.
When to Choose the GTX 1070 Ti
The GTX 1070 Ti fits budget-conscious users with local desktops for gaming or light compute. Its 8 GB GDDR5 and 11.2 TFLOPS FP32 suffice for inference on small models or non-AI tasks. At 180W TDP, it integrates into consumer power supplies without datacenter infrastructure.
Use Cases
The A100's 80 GB VRAM and 312 TFLOPS FP16 handle massive parameter counts and large batches. The 1070 Ti's 8 GB limits it to toy models.
A100's 2039 GB/s bandwidth supports high-throughput serving; 1070 Ti's 308 GB/s bottlenecks concurrent requests.
80 GB VRAM on A100 fits full model loading for efficient fine-tuning; 8 GB on 1070 Ti requires gradient checkpointing slowdowns.
A100 generates images faster with 312 TFLOPS FP16 versus 11.2 TFLOPS, plus higher batch sizes via 80 GB VRAM.
A100's 19.5 TFLOPS FP32 and NVLink interconnect excel in simulations; 1070 Ti's PCIe limits multi-GPU scaling.
Frequently Asked Questions
Is the A100 SXM4 80GB better than GTX 1070 Ti for machine learning?▾
Yes, the A100 offers 312 TFLOPS FP16 versus 11.2 TFLOPS and 80 GB VRAM versus 8 GB. This enables training large models without compromises. The 1070 Ti suits only small-scale tasks.
What is the VRAM difference between A100 SXM4 80GB and GTX 1070 Ti?▾
The A100 has 80 GB HBM2e; the 1070 Ti has 8 GB GDDR5. A100's capacity supports full model loading for LLMs. 1070 Ti requires quantization or sharding.
How does memory bandwidth compare on A100 vs 1070 Ti?▾
A100 provides 2039 GB/s; 1070 Ti offers 308 GB/s. Higher bandwidth on A100 sustains large batch training. Lower on 1070 Ti causes bottlenecks.
What are cloud prices for these GPUs?▾
A100 SXM4 80GB starts at $0.67 per hour, averaging $1.39 across 26 offers. GTX 1070 Ti has no live cloud offers. Local purchase applies for 1070 Ti.
Can GTX 1070 Ti handle AI inference like A100?▾
GTX 1070 Ti's 11.2 TFLOPS FP16 works for small models at low throughput. A100's 312 TFLOPS delivers 28 times faster inference. Use 1070 Ti only for prototypes.
What is the power consumption of A100 vs 1070 Ti?▾
A100 TDP is 400W; 1070 Ti is 180W. A100 suits datacenters; 1070 Ti fits consumer desktops. Higher TDP correlates with A100's performance lead.
Which is cheaper to rent, the A100 or the GTX 1070?▾
Cloud rental prices for both the A100 and GTX 1070 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 1070?▾
The A100 has 40 to 80 GB of HBM2e memory. The GTX 1070 has 8 GB of GDDR5 memory.
Can I find A100 and GTX 1070 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 1070?▾
The A100 uses the Ampere architecture (2020) while the GTX 1070 uses Pascal (2016). The A100 delivers 48.0x the FP16 throughput and 8.0x the memory bandwidth of the GTX 1070.