Specifications Compared
| Spec | A16 | RTX-5080 |
|---|---|---|
| TDP | 250W | 360W |
| VRAM | 16 GB | 16 GB |
| CUDA Cores | 2,560 | 10,752 |
| Memory Type | GDDR6 | GDDR7 |
| Architecture | Ampere | Blackwell |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 80 | 336 |
| FP16 Performance | 4.5 TFLOPS | 56.3 TFLOPS |
| FP32 Performance | 4.5 TFLOPS | 56.3 TFLOPS |
| Memory Bandwidth | 231 GB/s | 960 GB/s |
Performance Analysis
The RTX 5080 demonstrates superior raw compute: 56.3 TFLOPS in FP16 and FP32 dwarfs the A16's 4.5 TFLOPS, enabling up to 12 times faster matrix operations critical for deep learning. This gap translates to accelerated LLM training epochs and inference queries, where FP16 tensor cores handle half-precision workloads efficiently.
Memory bandwidth defines data throughput: the RTX 5080's 960 GB/s versus 231 GB/s supports larger batch sizes in training, reducing per-iteration time by minimizing bottlenecks. For inference, higher bandwidth sustains higher throughput under concurrent requests.
Power draw reflects capability differences: the A16 at 250W suits lighter envelopes, while the RTX 5080's 360W demands robust cooling but yields better performance per watt in modern Blackwell optimizations.
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 5080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 5080 16GB VRAM | 16GB | 0 vCPU 0GB RAM | 🌍global | $0.59/GPU/hr |
When to Choose the A16
The A16 excels in cost-stable, high-availability scenarios with 74 live offers averaging $0.48 per hour from $0.47 per hour. It fits legacy Ampere-optimized software or low-intensity inference where 4.5 TFLOPS suffices without overprovisioning. Lower 250W TDP aids power-constrained clusters prioritizing density over peak speed.
When to Choose the RTX 5080
Opt for the RTX 5080 in performance-critical tasks leveraging 56.3 TFLOPS FP16/FP32 and 960 GB/s bandwidth for rapid training or large-batch inference. Its Blackwell architecture from 2025 enhances efficiency in current AI frameworks, at averages of $0.38 per hour from $0.25 per hour despite limited 4 offers. Higher 360W TDP is justified for workloads demanding 12-fold compute uplift.
Use Cases
RTX 5080's 56.3 TFLOPS FP16 and 960 GB/s bandwidth enable 12 times faster training iterations than A16's 4.5 TFLOPS and 231 GB/s. Larger batches reduce overall time.
56.3 TFLOPS supports high-throughput serving on RTX 5080, far exceeding A16's 4.5 TFLOPS for concurrent queries. Bandwidth advantage handles peak loads.
Blackwell's 56.3 TFLOPS accelerates gradient computations over Ampere's 4.5 TFLOPS. 960 GB/s bandwidth fits larger models during adaptation.
RTX 5080's superior 56.3 TFLOPS FP16 generates images 12 times quicker than A16. Higher bandwidth speeds diffusion steps.
A16's 4.5 TFLOPS suffices for modest simulations at $0.48 per hour average. RTX 5080's 56.3 TFLOPS scales to complex HPC at $0.38 per hour.
Frequently Asked Questions
Which GPU has higher performance, A16 or RTX 5080?▾
The RTX 5080 leads with 56.3 TFLOPS in FP16 and FP32, compared to the A16's 4.5 TFLOPS. This provides over 12 times the compute power for AI tasks.
How do memory bandwidths compare between A16 and RTX 5080?▾
RTX 5080 offers 960 GB/s, quadrupling A16's 231 GB/s. Greater bandwidth supports bigger batches and faster data transfers in training.
What are the current cloud prices for A16 and RTX 5080?▾
A16 starts at $0.47 per hour, averaging $0.48 across 74 offers. RTX 5080 begins at $0.25 per hour, averaging $0.38 across 4 offers.
Which GPU uses less power, A16 or RTX 5080?▾
A16 consumes 250W TDP, lower than RTX 5080's 360W. A16 suits power-limited setups, while RTX 5080 prioritizes performance.
Are A16 and RTX 5080 both PCIe compatible?▾
Both support PCIe form factors without specialized interconnects. They integrate into standard cloud servers seamlessly.
What architectures power A16 and RTX 5080?▾
A16 uses Ampere from 2021 with GDDR6 VRAM. RTX 5080 employs Blackwell from 2025 with GDDR7 VRAM.
Which is cheaper to rent, the A16 or the RTX 5080?▾
Cloud rental prices for both the A16 and RTX 5080 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 5080?▾
The A16 has 16 GB of GDDR6 memory. The RTX 5080 has 16 GB of GDDR7 memory.
Can I find A16 and RTX 5080 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 5080?▾
The A16 uses the Ampere architecture (2021) while the RTX 5080 uses Blackwell (2025). The RTX 5080 delivers 12.5x the FP16 throughput and 4.2x the memory bandwidth of the A16.