Specifications Compared
| Spec | A30 | QUADRO-RTX-6000 |
|---|---|---|
| TDP | 165W | 260W |
| VRAM | 24 GB | 24 GB |
| CUDA Cores | 3,584 | 4,608 |
| Memory Type | HBM2 | GDDR6 |
| Architecture | Ampere | Turing |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | NVLink |
| Tensor Cores | 224 | 576 |
| FP16 Performance | 10.3 TFLOPS | 16.3 TFLOPS |
| FP32 Performance | 10.3 TFLOPS | 16.3 TFLOPS |
| FP64 Performance | 5.2 TFLOPS | |
| INT8 Performance | 165 TOPS | |
| Memory Bandwidth | 933 GB/s | 672 GB/s |
Performance Analysis
FP16 and FP32 performance metrics reveal a key disparity: the Quadro RTX 6000 achieves 16.3 TFLOPS in both, exceeding the A30's 10.3 TFLOPS. This advantage suits compute-intensive training phases where tensor core utilization drives throughput, particularly in FP32-dominant scientific simulations or legacy ML frameworks. However, real-world training efficiency also depends on memory access patterns.
The A30's 933 GB/s bandwidth significantly outpaces the Quadro RTX 6000's 672 GB/s, allowing larger batch sizes in inference workloads and reducing data transfer bottlenecks in transformer models. For LLM inference, this enables handling sequences up to 24 GB VRAM limits with higher throughput. Memory-bound tasks like fine-tuning large models benefit from HBM2's lower latency over GDDR6.
Power efficiency further differentiates them: the A30's 165 W TDP versus 260 W yields better performance per watt, critical for cloud or edge deployments with thermal constraints. Newer Ampere features in the A30 enhance sparsity acceleration, absent in Turing.
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When to Choose the A30
Opt for the A30 in data center environments prioritizing efficiency and memory bandwidth. Its 933 GB/s throughput supports larger batch sizes in LLM inference, while the 165 W TDP minimizes cooling costs in dense racks. Scenarios like multi-node training with NVLink scale effectively due to Ampere's 2021 optimizations.
Workloads involving high-resolution scientific computing or Stable Diffusion with extensive datasets favor the A30's HBM2 advantages over GDDR6.
When to Choose the Quadro RTX 6000
Select the Quadro RTX 6000 for workstation setups requiring peak FP32 compute. Its 16.3 TFLOPS outperforms the A30's 10.3 TFLOPS in rendering pipelines or FP-heavy simulations, leveraging Turing's mature drivers.
Budget-conscious users benefit from its proven reliability in CAD and visualization, despite higher 260 W power draw.
Use Cases
A30's 933 GB/s bandwidth handles large datasets better than 672 GB/s, supporting bigger batches despite 10.3 TFLOPS versus 16.3 TFLOPS.
Higher 933 GB/s bandwidth on A30 enables efficient high-throughput inference with 24 GB HBM2, outperforming GDDR6 in memory-bound scenarios.
Both offer 24 GB VRAM; Quadro RTX 6000's 16.3 TFLOPS aids compute phases, while A30's bandwidth suits data loading.
A30's Ampere architecture and 933 GB/s bandwidth accelerate diffusion models with large latents more effectively than Turing's 672 GB/s.
Quadro RTX 6000's 16.3 TFLOPS FP32 excels in simulation-heavy tasks over A30's 10.3 TFLOPS.
Frequently Asked Questions
Which GPU has higher memory bandwidth, A30 or Quadro RTX 6000?▾
The A30 provides 933 GB/s bandwidth with HBM2 memory, exceeding the Quadro RTX 6000's 672 GB/s GDDR6. This benefits memory-intensive AI workloads. Both share 24 GB VRAM capacity.
How do FP32 performance levels compare between A30 and Quadro RTX 6000?▾
Quadro RTX 6000 delivers 16.3 TFLOPS FP32, higher than A30's 10.3 TFLOPS. This favors compute-bound tasks like simulations. A30 compensates with efficiency at 165 W TDP versus 260 W.
Is the A30 more power efficient than Quadro RTX 6000?▾
Yes, A30's 165 W TDP is lower than 260 W on Quadro RTX 6000. It achieves 10.3 TFLOPS per GPU with better watts efficiency. This suits dense cloud deployments.
Do both support NVLink?▾
Both A30 and Quadro RTX 6000 include NVLink interconnect for multi-GPU scaling. They also use PCIe form factors. VRAM remains 24 GB on each.
Which is newer, A30 or Quadro RTX 6000?▾
A30 uses 2021 Ampere architecture, newer than 2018 Turing in Quadro RTX 6000. Ampere adds sparsity support. Bandwidth reaches 933 GB/s on A30.
Can A30 handle larger batches than Quadro RTX 6000?▾
A30's 933 GB/s bandwidth supports larger batches in training versus 672 GB/s on Quadro RTX 6000. HBM2 reduces latency. Both fit 24 GB models.
Which is cheaper to rent, the A30 or the Quadro RTX 6000?▾
Cloud rental prices for both the A30 and Quadro RTX 6000 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 A30 have compared to the Quadro RTX 6000?▾
The A30 has 24 GB of HBM2 memory. The Quadro RTX 6000 has 24 GB of GDDR6 memory.
Can I find A30 and Quadro RTX 6000 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 A30 and the Quadro RTX 6000?▾
The A30 uses the Ampere architecture (2021) while the Quadro RTX 6000 uses Turing (2018). The Quadro RTX 6000 delivers 1.6x the FP16 throughput and 1.4x the memory bandwidth of the A30.