Specifications Compared
| Spec | QUADRO-RTX-5000 | RTX-A2000 |
|---|---|---|
| TDP | 230W | 70W |
| VRAM | 16 GB | 6-12 GB |
| CUDA Cores | 3,072 | 3,328 |
| Memory Type | GDDR6 | GDDR6 |
| Architecture | Turing | Ampere |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 384 | 104 |
| FP16 Performance | 11.2 TFLOPS | 8 TFLOPS |
| FP32 Performance | 11.2 TFLOPS | 8 TFLOPS |
| Memory Bandwidth | 448 GB/s | 288 GB/s |
Performance Analysis
Compute performance favors the Quadro RTX 5000: its 11.2 TFLOPS in FP16 and FP32 exceeds the RTX A2000's 8 TFLOPS, enabling faster matrix operations in deep learning training. For model training, this delta translates to approximately 40% higher throughput on compute-bound tasks like backpropagation. The Ampere architecture in the RTX A2000, however, includes third-generation tensor cores that improve sparsity handling, potentially closing the gap in optimized inference workloads.
Memory capacity is a clear differentiator: 16 GB on the Quadro RTX 5000 supports larger batch sizes than the RTX A2000's 6-12 GB, reducing out-of-memory errors in LLM fine-tuning. Bandwidth at 448 GB/s versus 288 GB/s further aids the Quadro RTX 5000 in memory-intensive scenarios, allowing 55% higher data throughput for tasks with frequent weight loading. Smaller batches on the RTX A2000 suit inference, where lower latency per request matters over peak throughput.
Power draw impacts scalability: the Quadro RTX 5000's 230W TDP limits multi-GPU setups compared to the RTX A2000's 70W, which enables three times more instances per server rack. In real-world inference, this efficiency yields lower operational costs despite modest spec reductions.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
Quadro RTX 5000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Paperspace | NVIDIA Quadro RTX 5000 16GB VRAM | 16GB | 8 vCPU 30GB RAM 50GB Storage | New York | $0.82/GPU/hr | Available | ||
Paperspace | 2×NVIDIA Quadro RTX 5000 16GB VRAM | 16GB | 16 vCPU 60GB RAM 50GB Storage | New York | $0.82/GPU/hr $1.64/hr total (2×) | Available |
RTX A2000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA RTX A2000 12GB VRAM | 12GB | 6 vCPU 20GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the Quadro RTX 5000
Select the Quadro RTX 5000 for workloads demanding high VRAM and bandwidth, such as training large language models requiring over 12 GB. Its 16 GB GDDR6 and 448 GB/s handle batch sizes that exceed RTX A2000 limits, while 11.2 TFLOPS FP32 ensures 40% faster convergence in scientific simulations.
NVLink interconnect supports multi-GPU scaling unavailable on the RTX A2000, ideal for distributed training across nodes.
When to Choose the RTX A2000
The RTX A2000 excels in cost-sensitive deployments with its average $0.23 per hour pricing, one-third that of the Quadro RTX 5000's $0.82. Low 70W TDP facilitates high-density inference servers, maximizing instances per host.
For lightweight fine-tuning or Stable Diffusion, 6-12 GB VRAM and Ampere tensor cores deliver sufficient 8 TFLOPS performance at minimal cost.
Use Cases
Quadro RTX 5000's 16 GB VRAM supports larger models than RTX A2000's 12 GB maximum. Higher 448 GB/s bandwidth handles big batches effectively.
RTX A2000's lower $0.23/hr cost and 70W TDP enable scalable deployments. 8 TFLOPS suffices for batched requests with Ampere optimizations.
RTX A2000 manages most with 6-12 GB VRAM at low cost; Quadro RTX 5000 fits larger datasets via 16 GB. Choice depends on model size.
RTX A2000's Ampere architecture accelerates diffusion models efficiently at $0.06/hr low end. 288 GB/s bandwidth supports image generation pipelines.
Quadro RTX 5000's 11.2 TFLOPS FP32 outperforms RTX A2000's 8 TFLOPS for simulations. NVLink aids multi-GPU parallelization.
Frequently Asked Questions
Which GPU has more VRAM?▾
The Quadro RTX 5000 offers 16 GB GDDR6, surpassing the RTX A2000's 6-12 GB. This makes it better for memory-heavy tasks like large model training.
What are the current cloud prices?▾
Quadro RTX 5000 starts at $0.82 per hour average across 2 offers. RTX A2000 averages $0.23 per hour across 3 offers, with lows at $0.06.
How do FP32 performances compare?▾
Quadro RTX 5000 delivers 11.2 TFLOPS FP32, 40% above RTX A2000's 8 TFLOPS. This benefits compute-intensive workloads like simulations.
What is the power consumption difference?▾
RTX A2000 uses 70W TDP, versus Quadro RTX 5000's 230W. Lower power enables denser cloud deployments on the A2000.
Which has higher memory bandwidth?▾
Quadro RTX 5000 provides 448 GB/s, 55% more than RTX A2000's 288 GB/s. Bandwidth aids larger batch processing.
What architectures do they use?▾
Quadro RTX 5000 is Turing from 2018; RTX A2000 is Ampere from 2021. Ampere offers improved tensor cores despite lower peak TFLOPS.
Which is cheaper to rent, the Quadro RTX 5000 or the RTX A2000?▾
Cloud rental prices for both the Quadro RTX 5000 and RTX A2000 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 Quadro RTX 5000 have compared to the RTX A2000?▾
The Quadro RTX 5000 has 16 GB of GDDR6 memory. The RTX A2000 has 6 to 12 GB of GDDR6 memory.
Can I find Quadro RTX 5000 and RTX A2000 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 Quadro RTX 5000 and the RTX A2000?▾
The Quadro RTX 5000 uses the Turing architecture (2018) while the RTX A2000 uses Ampere (2021). The Quadro RTX 5000 delivers 1.4x the FP16 throughput and 1.6x the memory bandwidth of the RTX A2000.