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 40GB outperforms the GTX 1070 Ti dramatically in compute capabilities tailored for AI. Its FP16 performance reaches 312 TFLOPS thanks to tensor cores, compared to the 1070 Ti's 8.9 TFLOPS, accelerating mixed-precision training and inference by orders of magnitude. FP32 performance of 19.5 TFLOPS on the A100 also surpasses the 1070 Ti's 8.9 TFLOPS, benefiting single-precision scientific simulations.
Memory specifications highlight a key bottleneck for the 1070 Ti: 8 GB GDDR5 limits batch sizes in deep learning to small models, whereas the A100's 40 GB HBM2e supports massive datasets. The A100's 2039 GB/s bandwidth versus 256 GB/s reduces data transfer latency, enabling larger effective batch sizes and faster training convergence in real-world neural network workloads.
Power efficiency differs: the A100's 400W TDP suits datacenter cooling, while the 1070 Ti's 180W fits consumer desktops. These specs translate to the A100 completing LLM training epochs in minutes that take hours on the 1070 Ti.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 SXM4 40GB
| 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×) |
When to Choose the A100 SXM4 40GB
Choose the A100 SXM4 40GB for professional AI and HPC tasks requiring high throughput. Its 312 TFLOPS FP16 and 40 GB VRAM excel in training large language models or fine-tuning transformers, where the GTX 1070 Ti's 8 GB VRAM causes out-of-memory errors. Cloud availability at $1.00 per hour average supports scalable deployments without upfront hardware costs.
When to Choose the GTX 1070 Ti
Select the GTX 1070 Ti for budget-conscious local gaming or lightweight compute on existing desktops. Its 8.9 TFLOPS FP32 and 180W TDP suffice for 1080p gaming or basic inference on small models under 8 GB. Absence of cloud pricing favors it when avoiding rental fees for non-intensive, intermittent use.
Use Cases
The A100's 312 TFLOPS FP16 and 40 GB VRAM handle large-scale LLM training with massive batches. The 1070 Ti's 8 GB VRAM limits model sizes severely.
A100 supports high-throughput inference via 2039 GB/s bandwidth for real-time serving. GTX 1070 Ti struggles with models exceeding 8 GB.
40 GB HBM2e on A100 enables fine-tuning of large models without truncation. 1070 Ti's 8.9 TFLOPS FP16 is inadequate for efficient mixed-precision tuning.
A100 generates images rapidly with 312 TFLOPS FP16 for high-resolution Stable Diffusion. GTX 1070 Ti works for basic 512x512 but slows on larger outputs.
A100's 19.5 TFLOPS FP32 and NVLink interconnect accelerate simulations. 1070 Ti's PCIe limits multi-GPU scaling.
Frequently Asked Questions
Is the A100 better than GTX 1070 Ti for deep learning?▾
Yes, the A100 SXM4 40GB excels with 312 TFLOPS FP16 versus 8.9 TFLOPS on the 1070 Ti. Its 40 GB VRAM supports larger models, preventing out-of-memory issues common with the 1070 Ti's 8 GB.
How much faster is A100 VRAM bandwidth than GTX 1070 Ti?▾
The A100 offers 2039 GB/s bandwidth, about eight times the GTX 1070 Ti's 256 GB/s. This enables larger batch sizes and quicker data loading in training workflows.
Can GTX 1070 Ti run Stable Diffusion?▾
Yes, the GTX 1070 Ti handles basic Stable Diffusion at 512x512 resolutions with its 8.9 TFLOPS FP32. However, it slows significantly compared to A100's 312 TFLOPS FP16 for higher quality or batch generation.
What is the power consumption difference?▾
The A100 SXM4 40GB has a 400W TDP, suited for datacenters. The GTX 1070 Ti uses 180W, ideal for consumer power supplies.
Is A100 available on cloud with pricing?▾
Yes, NVIDIA A100 SXM4 40GB clouds from $1.00 per hour, averaging $2.63 per hour across five offers. GTX 1070 Ti has no live cloud availability.
Which has more VRAM: A100 or GTX 1070 Ti?▾
The A100 provides 40 GB HBM2e, five times the GTX 1070 Ti's 8 GB GDDR5. This gap is critical for modern AI models exceeding 8 GB.
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.