Specifications Compared
| Spec | QUADRO-RTX-8000 | RTX-A2000 |
|---|---|---|
| TDP | 260W | 70W |
| VRAM | 48 GB | 6-12 GB |
| CUDA Cores | 4,608 | 3,328 |
| Memory Type | GDDR6 | GDDR6 |
| Architecture | Turing | Ampere |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 576 | 104 |
| FP16 Performance | 16.3 TFLOPS | 8 TFLOPS |
| FP32 Performance | 16.3 TFLOPS | 8 TFLOPS |
| Memory Bandwidth | 672 GB/s | 288 GB/s |
Performance Analysis
The Quadro RTX 8000's 16.3 TFLOPS FP16 and FP32 performance doubles the RTX A2000's 8 TFLOPS, enabling faster matrix operations critical for deep learning training and inference. In training scenarios, this FP32 advantage accelerates gradient computations; for inference, FP16 boosts throughput on half-precision models. Real-world impact includes roughly twice the speed on compute-bound workloads like neural network forward passes.
Memory specifications define practical limits: 48 GB VRAM on the Quadro RTX 8000 supports massive models or large batch sizes, such as 8x larger than the RTX A2000's 6 GB minimum. The 672 GB/s bandwidth versus 288 GB/s sustains higher data transfer rates, reducing bottlenecks in memory-bound tasks and allowing batch sizes up to 2.3 times larger without swapping.
Power differences matter in cloud scaling: the 260W TDP demands robust cooling and higher costs, while 70W enables dense deployments. Ampere's architectural improvements yield better efficiency per watt despite lower peaks.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
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 8000
The Quadro RTX 8000 excels in scenarios requiring extreme memory capacity, such as training large language models exceeding 12 GB VRAM or scientific simulations with 48 GB datasets. Its 672 GB/s bandwidth and NVLink interconnect optimize multi-GPU setups for distributed computing where data locality is vital.
Professionals handling high-resolution rendering or complex CAD with 16.3 TFLOPS FP32 performance select it over lower-spec alternatives, accepting the 260W TDP for unmatched scale.
When to Choose the RTX A2000
The RTX A2000 suits budget-conscious cloud users with its pricing from $0.06 per hour and average $0.23 per hour across three offers. Low 70W TDP enables cost-effective, dense inference servers for models fitting within 6-12 GB VRAM.
Entry-level AI development or lightweight visualization benefits from Ampere architecture's efficiency, where 8 TFLOPS suffices without the Quadro RTX 8000's overhead.
Use Cases
The Quadro RTX 8000's 48 GB VRAM handles large model parameters and gradients that exceed the RTX A2000's 6-12 GB. Its 16.3 TFLOPS FP32 doubles training speed on compute-heavy batches.
48 GB VRAM supports high-concurrency inference for large LLMs without quantization losses. 672 GB/s bandwidth enables larger batch sizes than the RTX A2000's 288 GB/s.
RTX A2000 suffices for models under 12 GB with 8 TFLOPS efficiency at $0.06 per hour. Quadro RTX 8000 accelerates larger fine-tunes via 48 GB VRAM and 16.3 TFLOPS.
RTX A2000's 6-12 GB VRAM fits typical diffusion models, with 70W TDP for cost-effective generation at $0.23 per hour average. Higher specs on Quadro RTX 8000 remain underutilized.
Quadro RTX 8000's 48 GB VRAM and NVLink manage large simulations or datasets. 16.3 TFLOPS FP32 outperforms RTX A2000's 8 TFLOPS on precision-bound HPC tasks.
Frequently Asked Questions
Which GPU has more VRAM?▾
The Quadro RTX 8000 provides 48 GB GDDR6 VRAM, far exceeding the RTX A2000's 6-12 GB. This enables larger models on the Quadro RTX 8000. Bandwidth follows suit at 672 GB/s versus 288 GB/s.
What are the performance differences?▾
Quadro RTX 8000 achieves 16.3 TFLOPS in FP16 and FP32, double the RTX A2000's 8 TFLOPS. This translates to faster training and inference. Architecture dates confirm Turing 2018 versus Ampere 2021.
Which is more power efficient?▾
RTX A2000 consumes 70W TDP, versus 260W for Quadro RTX 8000. Lower power supports dense cloud deployments. Pricing reflects this at $0.06 per hour minimum for RTX A2000.
Does Quadro RTX 8000 support NVLink?▾
Yes, Quadro RTX 8000 includes NVLink for multi-GPU scaling. RTX A2000 lacks this interconnect. Both use PCIe form factors.
What is the cloud pricing for these GPUs?▾
RTX A2000 offers start at $0.06 per hour, averaging $0.23 per hour across three providers. Quadro RTX 8000 has no live offers currently. Availability favors RTX A2000.
Which is better for AI training?▾
Quadro RTX 8000 excels with 48 GB VRAM and 16.3 TFLOPS FP32 for large-scale training. RTX A2000 handles smaller jobs efficiently at lower cost. Choice depends on model size.
Which is cheaper to rent, the Quadro RTX 8000 or the RTX A2000?▾
Cloud rental prices for both the Quadro RTX 8000 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 8000 have compared to the RTX A2000?▾
The Quadro RTX 8000 has 48 GB of GDDR6 memory. The RTX A2000 has 6 to 12 GB of GDDR6 memory.
Can I find Quadro RTX 8000 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 8000 and the RTX A2000?▾
The Quadro RTX 8000 uses the Turing architecture (2018) while the RTX A2000 uses Ampere (2021). The Quadro RTX 8000 delivers 2.0x the FP16 throughput and 2.3x the memory bandwidth of the RTX A2000.