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
Memory capacity creates the most profound impact: 40 GB HBM2e on the A100 SXM4 40GB enables handling of large models and datasets, while 8 GB GDDR5 on the GTX 1070 limits it to smaller batches or models. Bandwidth follows suit at 2039 GB/s for the A100 versus 256 GB/s for the GTX 1070, allowing the A100 to process data 8 times faster and support larger batch sizes in training without memory bottlenecks.
FP16 performance favors the A100 decisively at 312 TFLOPS against 6.5 TFLOPS on the GTX 1070, accelerating mixed-precision training common in deep learning by nearly 48 times. FP32 throughput of 19.5 TFLOPS on the A100 exceeds the GTX 1070's 6.5 TFLOPS by a factor of 3, benefiting inference and scientific simulations requiring single precision. In real-world terms, the A100 completes large language model training epochs in minutes where the GTX 1070 requires hours.
Higher TDP of 400W on the A100 reflects its datacenter optimization, contrasting the 150W efficiency of the GTX 1070 for desktop use. These specs translate to the A100 dominating AI inference latency and throughput, while the GTX 1070 suffices for lightweight prototyping.
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 | 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 | 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×) |
When to Choose the A100 SXM4 40GB
The NVIDIA A100 SXM4 40GB excels in professional AI workloads requiring high VRAM and throughput. It suits large-scale LLM training or inference where 40 GB HBM2e and 312 TFLOPS FP16 handle models exceeding 8 GB, such as those with billions of parameters. Cloud pricing from $1.00 per hour makes it ideal for bursty enterprise tasks on NVLink clusters.
Scientific computing benefits from 2039 GB/s bandwidth for simulations with massive datasets, outperforming the GTX 1070 by orders of magnitude in batch processing.
When to Choose the GTX 1070
The NVIDIA GeForce GTX 1070 fits budget-conscious hobbyists or legacy setups with low-power needs at 150W TDP. It handles light gaming or basic ML prototyping where 8 GB GDDR5 and 6.5 TFLOPS suffice for small models under 4 GB. Local desktop deployment avoids cloud costs, as no live offers exist.
Entry-level Stable Diffusion or fine-tuning on modest datasets works adequately without the A100's overhead.
Use Cases
The A100's 40 GB HBM2e VRAM and 312 TFLOPS FP16 enable training of large models with billion-scale parameters. The GTX 1070's 8 GB GDDR5 causes out-of-memory errors for such tasks.
2039 GB/s bandwidth on the A100 supports high-throughput inference with large batches. The GTX 1070's 256 GB/s limits concurrency to small-scale deployments.
19.5 TFLOPS FP32 and 40 GB VRAM accelerate fine-tuning of mid-to-large models efficiently. GTX 1070 handles only tiny models due to 6.5 TFLOPS and 8 GB constraints.
A100's high FP16 performance generates images rapidly at high resolutions with large batches. GTX 1070 manages basic generations but slows on complex prompts.
2039 GB/s bandwidth processes vast datasets in simulations without bottlenecks. GTX 1070's 256 GB/s restricts it to smaller-scale computations.
Frequently Asked Questions
What is the VRAM difference between A100 SXM4 40GB and GTX 1070?▾
The A100 SXM4 40GB provides 40 GB HBM2e VRAM. The GTX 1070 offers 8 GB GDDR5. This 5 times greater capacity on the A100 supports larger models in AI tasks.
How does FP16 performance compare?▾
A100 achieves 312 TFLOPS in FP16. GTX 1070 delivers 6.5 TFLOPS. The A100 is nearly 48 times faster for half-precision training and inference.
What are the cloud prices for these GPUs?▾
A100 SXM4 40GB starts at $1.00 per hour with an average of $2.63 per hour across five offers. No live cloud offers exist for GTX 1070.
Is GTX 1070 suitable for machine learning?▾
GTX 1070 manages basic ML with 6.5 TFLOPS FP32 and 8 GB VRAM. It struggles with modern workloads needing more than 8 GB or high throughput.
What is the memory bandwidth gap?▾
A100 features 2039 GB/s bandwidth. GTX 1070 has 256 GB/s. This enables the A100 to handle 8 times larger data flows for batch processing.
Which has higher power consumption?▾
A100 TDP is 400W for datacenter use. GTX 1070 TDP is 150W, suiting desktops. Higher TDP correlates with A100's superior 312 TFLOPS FP16.
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.