Specifications Compared
| Spec | A16 | RTX-2080 |
|---|---|---|
| TDP | 250W | 215W |
| VRAM | 16 GB | 8-11 GB |
| CUDA Cores | 2,560 | 2,944 |
| Memory Type | GDDR6 | GDDR6 |
| Architecture | Ampere | Turing |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 80 | 368 |
| FP16 Performance | 4.5 TFLOPS | 10.1 TFLOPS |
| FP32 Performance | 4.5 TFLOPS | 10.1 TFLOPS |
| Memory Bandwidth | 231 GB/s | 616 GB/s |
Performance Analysis
The RTX 2080 Ti outperforms the A16 in raw compute with 10.1 TFLOPS FP32 compared to 4.5 TFLOPS, enabling faster model training and inference in single-precision workloads common in deep learning pipelines. This FP16 and FP32 parity at higher rates on the RTX 2080 Ti accelerates tensor operations in frameworks like TensorFlow or PyTorch, reducing epoch times by over 50 percent in benchmarks tied to FLOPS. Memory bandwidth presents a key delta: 616 GB/s on RTX 2080 Ti versus 231 GB/s on A16 supports larger batch sizes in training, minimizing data loading bottlenecks and improving GPU utilization up to 2.5 times in memory-intensive tasks. The A16 counters with 16 GB VRAM against 11 GB maximum on RTX 2080 Ti, accommodating larger models or multi-instance setups without swapping to host memory. Power draw favors RTX 2080 Ti slightly at 215 W versus 250 W, yielding better efficiency per watt at 47 TFLOPS per kW compared to 18 TFLOPS per kW. Overall, RTX 2080 Ti excels in throughput-bound scenarios, while A16 suits VRAM-constrained deployments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A16
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | 8×NVIDIA A16 64GB VRAM | 64GB | 48 vCPU 496GB RAM 1500GB Storage | Singapore | $0.47/GPU/hr $3.77/hr total (8×) | Available | ||
Vultr | 8×NVIDIA A16 64GB VRAM | 64GB | 48 vCPU 496GB RAM 1500GB Storage | Atlanta | $0.47/GPU/hr $3.77/hr total (8×) | Available | ||
Vultr | 8×NVIDIA A16 64GB VRAM | 64GB | 48 vCPU 496GB RAM 1500GB Storage | Bangalore | $0.47/GPU/hr $3.77/hr total (8×) | Available | ||
Vultr | 2×NVIDIA A16 64GB VRAM | 64GB | 12 vCPU 128GB RAM 700GB Storage | Bangalore | $0.47/GPU/hr $0.94/hr total (2×) | Available | ||
Vultr | 4×NVIDIA A16 64GB VRAM | 64GB | 24 vCPU 256GB RAM 1200GB Storage | Atlanta | $0.47/GPU/hr $1.88/hr total (4×) | Available |
RTX 2080 Ti
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA GeForce RTX 2080 Ti 11GB VRAM | 11GB | 32 vCPU 63GB RAM 1273GB Storage | Maryland | $0.13/GPU/hr | Available |
When to Choose the A16
Opt for the NVIDIA A16 in virtual GPU environments requiring high VRAM density: its 16 GB GDDR6 handles multi-user inference or graphics workloads better than the RTX 2080 Ti's 11 GB maximum. The Ampere architecture from 2021 supports modern features like improved MIG for partitioning, ideal for cloud providers serving 77 live offers at $0.48 per hour average. Choose A16 for stable, enterprise-grade VDI where availability trumps peak performance.
When to Choose the RTX 2080 Ti
Select the NVIDIA GeForce RTX 2080 Ti for budget-sensitive compute where high throughput matters: 10.1 TFLOPS FP32 and 616 GB/s bandwidth outperform A16's 4.5 TFLOPS and 231 GB/s at $0.11 per hour average. Its NVLink interconnect aids multi-GPU scaling in training setups. Prioritize RTX 2080 Ti for cost-per-FLOP efficiency in short bursts or gaming-adjacent ML tasks.
Use Cases
RTX 2080 Ti's 10.1 TFLOPS FP32 and 616 GB/s bandwidth enable faster training epochs with larger batches than A16's 4.5 TFLOPS and 231 GB/s.
A16's 16 GB VRAM supports larger models for batched inference without offloading, outperforming RTX 2080 Ti's 11 GB limit.
Higher 10.1 TFLOPS FP16 on RTX 2080 Ti accelerates fine-tuning iterations compared to A16's 4.5 TFLOPS, with pricing at $0.11 per hour.
RTX 2080 Ti offers superior 616 GB/s bandwidth for generation speed; A16 provides 16 GB VRAM for higher resolutions.
RTX 2080 Ti's 10.1 TFLOPS FP32 and lower 215 W TDP deliver efficient simulations versus A16's lower specs.
Frequently Asked Questions
Which GPU has more VRAM: A16 or RTX 2080 Ti?▾
The A16 provides 16 GB GDDR6 VRAM, exceeding the RTX 2080 Ti's 8 to 11 GB range. This benefits large model hosting. Bandwidth favors RTX 2080 Ti at 616 GB/s over 231 GB/s.
What is the performance difference in TFLOPS?▾
RTX 2080 Ti achieves 10.1 TFLOPS in FP16 and FP32, more than double A16's 4.5 TFLOPS per precision. This impacts training speed directly. Architectures differ: Ampere for A16, Turing for RTX 2080 Ti.
How do cloud prices compare for A16 and RTX 2080 Ti?▾
A16 rents from $0.47 per hour averaging $0.48 across 77 offers; RTX 2080 Ti starts at $0.06 averaging $0.11 across 6 offers. Price per TFLOPS heavily favors RTX 2080 Ti. Availability is higher for A16.
Which has higher memory bandwidth?▾
RTX 2080 Ti leads with 616 GB/s versus A16's 231 GB/s. Larger batches fit in training. VRAM compensates on A16 at 16 GB.
What are the TDPs of these GPUs?▾
A16 consumes 250 W; RTX 2080 Ti uses 215 W. Efficiency per watt is higher on RTX 2080 Ti at 47 TFLOPS per kW. Both use PCIe form factors.
Does RTX 2080 Ti support NVLink?▾
Yes, RTX 2080 Ti includes NVLink for multi-GPU communication; A16 lacks it. This aids scaling in clusters. A16 focuses on PCIe single-node use.
Which is cheaper to rent, the A16 or the RTX 2080?▾
Cloud rental prices for both the A16 and RTX 2080 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 A16 have compared to the RTX 2080?▾
The A16 has 16 GB of GDDR6 memory. The RTX 2080 has 8 to 11 GB of GDDR6 memory.
Can I find A16 and RTX 2080 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 A16 and the RTX 2080?▾
The A16 uses the Ampere architecture (2021) while the RTX 2080 uses Turing (2018). The RTX 2080 delivers 2.2x the FP16 throughput and 2.7x the memory bandwidth of the A16.