Specifications Compared
| Spec | A30 | RTX-2060 |
|---|---|---|
| TDP | 165W | 160W |
| VRAM | 24 GB | 6-12 GB |
| CUDA Cores | 3,584 | 1,920 |
| Memory Type | HBM2 | GDDR6 |
| Architecture | Ampere | Turing |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 224 | 240 |
| FP16 Performance | 10.3 TFLOPS | 6.5 TFLOPS |
| FP32 Performance | 10.3 TFLOPS | 6.5 TFLOPS |
| FP64 Performance | 5.2 TFLOPS | |
| INT8 Performance | 165 TOPS | |
| Memory Bandwidth | 933 GB/s | 336 GB/s |
Performance Analysis
The A30's 10.3 TFLOPS FP16 and FP32 throughput outpaces the RTX 2060 SUPER's 7.2 TFLOPS: this 43 percent advantage accelerates deep learning operations like matrix multiplications in model training and inference. In mixed-precision training, higher FP16 performance on the A30 reduces computation time for neural network forward and backward passes.
Memory bandwidth marks a key differentiator at 933 GB/s for the A30 versus 448 GB/s on the RTX 2060 SUPER: the A30 sustains larger batch sizes in memory-bound tasks, minimizing data transfer bottlenecks during training epochs. The A30's 24 GB HBM2 VRAM versus 8 GB GDDR6 enables handling of larger models without swapping, improving inference latency for production deployments. These specs position the A30 for scalable AI pipelines.
Live Cloud Pricing
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When to Choose the A30
Professionals select the A30 for memory-intensive workloads such as LLM inference or training where 24 GB HBM2 exceeds the RTX 2060 SUPER's 8 GB limit. NVLink support facilitates multi-GPU configurations for distributed training, unavailable on the consumer card. Its 933 GB/s bandwidth supports high-throughput scientific simulations.
When to Choose the RTX 2060 SUPER
Budget-conscious users opt for the RTX 2060 SUPER in gaming or lightweight ML tasks like fine-tuning small models, where 8 GB GDDR6 and 448 GB/s bandwidth suffice. Desktop enthusiasts prefer its accessibility for Stable Diffusion generation without enterprise overhead. Lower acquisition costs suit hobbyist inference on modest datasets.
Use Cases
The A30's 24 GB VRAM accommodates large language models that exceed the RTX 2060 SUPER's 8 GB capacity. Its 933 GB/s bandwidth enables larger batch sizes for efficient training.
A30 supports inference on models requiring over 8 GB VRAM without quantization compromises. Higher 10.3 TFLOPS FP16 performance delivers lower latency.
24 GB HBM2 on A30 allows fine-tuning mid-sized models with full batch sizes. 43 percent higher FP32 throughput speeds up iterations versus 7.2 TFLOPS.
RTX 2060 SUPER's 8 GB GDDR6 handles standard resolutions adequately. A30 offers faster generation via 933 GB/s bandwidth for complex prompts.
A30's NVLink and 10.3 TFLOPS FP32 suit parallel simulations. Superior memory capacity processes large datasets beyond 8 GB limits.
Frequently Asked Questions
Which GPU has more VRAM: A30 or RTX 2060 SUPER?▾
The A30 provides 24 GB HBM2 VRAM, far exceeding the RTX 2060 SUPER's 8 GB GDDR6. This difference favors the A30 for large-model AI tasks. HBM2 also offers lower latency access.
Is the A30 faster than RTX 2060 SUPER in compute?▾
The A30 achieves 10.3 TFLOPS in FP16 and FP32, a 43 percent gain over the RTX 2060 SUPER's 7.2 TFLOPS. This boosts training and inference speeds. Bandwidth at 933 GB/s versus 448 GB/s amplifies real-world gains.
What are the power requirements for A30 vs RTX 2060 SUPER?▾
A30 has a 165 W TDP, slightly lower than the RTX 2060 SUPER's 175 W. Both fit standard PCIe power delivery. Efficiency favors A30 in dense cloud deployments.
Which is better for deep learning: A30 or RTX 2060 SUPER?▾
A30 excels with 24 GB VRAM and 933 GB/s bandwidth for memory-heavy deep learning. RTX 2060 SUPER suits smaller models under 8 GB. NVLink on A30 enables scaling.
Can A30 and RTX 2060 SUPER connect in multi-GPU setups?▾
A30 supports NVLink for high-speed multi-GPU communication, absent on RTX 2060 SUPER. PCIe limits apply to both otherwise. This makes A30 preferable for distributed training.
What architectures do A30 and RTX 2060 SUPER use?▾
A30 employs Ampere from 2021 with advanced tensor cores. RTX 2060 SUPER uses Turing from 2019. Ampere delivers 43 percent higher FP32 at 10.3 TFLOPS versus 7.2 TFLOPS.
Which is cheaper to rent, the A30 or the RTX 2060?▾
Cloud rental prices for both the A30 and RTX 2060 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 RTX 2060?▾
The A30 has 24 GB of HBM2 memory. The RTX 2060 has 6 to 12 GB of GDDR6 memory.
Can I find A30 and RTX 2060 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 RTX 2060?▾
The A30 uses the Ampere architecture (2021) while the RTX 2060 uses Turing (2019). The A30 delivers 1.6x the FP16 throughput and 2.8x the memory bandwidth of the RTX 2060.