Specifications Compared
| Spec | A40 | GTX-1080 |
|---|---|---|
| TDP | 300W | 180W |
| VRAM | 48 GB | 8-11 GB |
| CUDA Cores | 10,752 | 2,560 |
| Memory Type | GDDR6 | GDDR5X |
| Architecture | Ampere | Pascal |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 336 | |
| FP16 Performance | 37.4 TFLOPS | 8.9 TFLOPS |
| FP32 Performance | 37.4 TFLOPS | 8.9 TFLOPS |
| FP64 Performance | 0.6 TFLOPS | |
| INT8 Performance | 299 TOPS | |
| Memory Bandwidth | 696 GB/s | 320 GB/s |
Performance Analysis
The A40 delivers 37.4 TFLOPS in FP32, over four times the GTX 1080's 8.9 TFLOPS. This gap accelerates machine learning training: a workload taking one hour on GTX 1080 might finish in 15 minutes on A40. Equal FP16 and FP32 rates on both indicate balanced precision handling, but A40's scale supports complex models without precision trade-offs.
VRAM disparity defines real-world limits: A40's 48 GB handles batch sizes 4-6 times larger than GTX 1080's 8-11 GB, minimizing data loading overhead in training loops. The A40's 696 GB/s bandwidth, more than double the 320 GB/s, prevents bottlenecks during large-batch inference or diffusion model generation. Lower TDP on GTX 1080 (180W versus 300W) aids power-sensitive setups, yet overall throughput favors A40 for demanding compute.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A40
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA RTX A4000 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Tallinn, Harjumaa | $0.08/GPU/hr | Available | ||
 Vast.ai | 8×NVIDIA RTX A4000 16GB VRAM | 16GB | 80 vCPU 201GB RAM 1698GB Storage | United Kingdom | $0.15/GPU/hr $1.17/hr total (8×) | Available | ||
 Hyperstack | 4×NVIDIA RTX A4000 16GB VRAM | 16GB | 16 vCPU 86GB RAM 500GB Storage | Norway | $0.15/GPU/hr $0.60/hr total (4×) | Available | ||
Hyperstack | 2×NVIDIA RTX A4000 16GB VRAM | 16GB | 8 vCPU 43GB RAM 200GB Storage | Norway | $0.15/GPU/hr $0.30/hr total (2×) | Available | ||
Hyperstack | NVIDIA RTX A4000 16GB VRAM | 16GB | 4 vCPU 21GB RAM 100GB Storage | Norway | $0.15/GPU/hr | Available |
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 A40
Choose the A40 for AI workloads needing high VRAM capacity. Its 48 GB GDDR6 supports training large language models with batch sizes infeasible on 8-11 GB GTX 1080. Professional rendering or scientific simulations benefit from 37.4 TFLOPS FP32 and NVLink interconnect for multi-GPU scaling.
Cloud users prioritizing speed over initial cost select A40, as 696 GB/s bandwidth sustains high-throughput inference.
When to Choose the GTX 1080
The GTX 1080 fits budget inference or prototyping on small models. Average $0.45/hr pricing undercuts A40's $1.26/hr, with 180W TDP suiting low-power instances. Its 8-11 GB VRAM handles lightweight fine-tuning where 8.9 TFLOPS suffices.
Legacy gaming or simple compute tasks favor GTX 1080 for cost efficiency across limited cloud offers.
Use Cases
A40's 48 GB VRAM supports large batch sizes essential for efficient LLM training. GTX 1080's 8-11 GB limits model scale and increases overhead.
A40 handles high-concurrency inference with 37.4 TFLOPS and 696 GB/s bandwidth. GTX 1080's lower specs restrict throughput for production loads.
Fine-tuning mid-sized models requires A40's 48 GB capacity for full precision. GTX 1080's 8-11 GB forces quantization or smaller batches.
A40 generates higher-resolution images faster via 37.4 TFLOPS FP16. GTX 1080 manages basic tasks but bottlenecks on complex prompts.
A40's 37.4 TFLOPS FP32 excels in simulations needing high memory bandwidth of 696 GB/s. GTX 1080's 8.9 TFLOPS suits only small-scale computations.
Frequently Asked Questions
Which GPU has more VRAM: A40 or GTX 1080?▾
The A40 provides 48 GB GDDR6 VRAM. GTX 1080 offers 8-11 GB GDDR5X. This makes A40 suitable for larger models.
How do their compute performances compare?▾
A40 achieves 37.4 TFLOPS in FP16 and FP32. GTX 1080 delivers 8.9 TFLOPS in both. A40 offers over four times the performance.
What are the cloud rental prices?▾
A40 starts at $0.24/hr with average $1.26/hr across 23 offers. GTX 1080 starts at $0.30/hr with average $0.45/hr across 2 offers. GTX 1080 appears cheaper on average.
Which has higher memory bandwidth?▾
A40's bandwidth reaches 696 GB/s. GTX 1080 provides 320 GB/s. A40 better supports large batch processing.
What is the TDP difference?▾
A40 consumes 300W TDP. GTX 1080 uses 180W. Lower TDP on GTX 1080 aids power-constrained environments.
Do they support the same form factors?▾
Both use PCIe form factors. A40 adds NVLink interconnect, absent on GTX 1080, for multi-GPU setups.
Which is cheaper to rent, the A40 or the GTX 1080?▾
Cloud rental prices for both the A40 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 A40 have compared to the GTX 1080?▾
The A40 has 48 GB of GDDR6 memory. The GTX 1080 has 8 to 11 GB of GDDR5X memory.
Can I find A40 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 A40 and the GTX 1080?▾
The A40 uses the Ampere architecture (2020) while the GTX 1080 uses Pascal (2016). The A40 delivers 4.2x the FP16 throughput and 2.2x the memory bandwidth of the GTX 1080.