Specifications Compared
| Spec | A30 | RTX-4070 |
|---|---|---|
| TDP | 165W | 200W |
| VRAM | 24 GB | 12 GB |
| CUDA Cores | 3,584 | 5,888 |
| Memory Type | HBM2 | GDDR6X |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 224 | 184 |
| FP16 Performance | 10.3 TFLOPS | 29.1 TFLOPS |
| FP32 Performance | 10.3 TFLOPS | 29.1 TFLOPS |
| FP64 Performance | 5.2 TFLOPS | |
| INT8 Performance | 165 TOPS | 466 TOPS |
| Memory Bandwidth | 933 GB/s | 504 GB/s |
Performance Analysis
The RTX 4070 SUPER achieves markedly higher compute throughput: 35.5 TFLOPS in FP16 and FP32 dwarfs the A30's 10.3 TFLOPS. This disparity accelerates training and inference phases in workloads dependent on shader performance, such as fine-tuning mid-sized models or scientific computations requiring rapid floating-point operations.
Memory capacity and speed favor the A30 decisively: 24 GB HBM2 at 933 GB/s bandwidth accommodates larger batch sizes during deep learning training, minimizing data transfer bottlenecks. The RTX 4070 SUPER's 12 GB GDDR6X at 504 GB/s constrains it to smaller batches or models, potentially slowing large-scale LLM processing.
Architectural advancements in Ada Lovelace provide the RTX 4070 SUPER with superior efficiency features, while the A30's NVLink interconnect enables multi-GPU configurations absent on the RTX 4070 SUPER.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 4070 SUPER
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4070 Ti 12GB VRAM | 12GB | 6 vCPU 30GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the A30
The A30 stands out for memory-intensive applications: its 24 GB HBM2 capacity supports training or inference on large language models that exceed the RTX 4070 SUPER's 12 GB limit. The 933 GB/s bandwidth sustains high batch sizes, enhancing throughput in data center pipelines.
Lower TDP of 165 W reduces operational costs, and NVLink connectivity facilitates scaling across multiple GPUs for distributed workloads.
When to Choose the RTX 4070 SUPER
The RTX 4070 SUPER excels in compute-dominated tasks: 35.5 TFLOPS FP16 and FP32 performance triples the A30's 10.3 TFLOPS, hastening fine-tuning and inference on models under 12 GB VRAM. Ada Lovelace architecture incorporates optimized tensor cores for AI generation workflows.
It suits hybrid use cases like Stable Diffusion or gaming-accelerated simulations, where newer features and potential cost advantages in cloud rentals prevail over the A30's memory strengths.
Use Cases
The A30's 24 GB HBM2 handles massive datasets and large batch sizes essential for LLM training. Its 933 GB/s bandwidth outperforms the RTX 4070 SUPER's 504 GB/s, reducing memory bottlenecks.
RTX 4070 SUPER's 35.5 TFLOPS FP16/FP32 enables quicker inference on models under 12 GB. Higher compute speed outweighs the A30's memory advantage for typical inference loads.
Fine-tuning mid-sized LLMs benefits from the RTX 4070 SUPER's 35.5 TFLOPS versus 10.3 TFLOPS on A30. Most fine-tuning fits within 12 GB VRAM.
Ada Lovelace optimizations in RTX 4070 SUPER boost image generation speeds at 35.5 TFLOPS. Consumer features align better with creative AI tasks than A30's enterprise focus.
A30's 933 GB/s bandwidth and 24 GB HBM2 excel in high-memory simulations. NVLink support aids multi-GPU scientific scaling unavailable on RTX 4070 SUPER.
Frequently Asked Questions
Which GPU has more VRAM, A30 or RTX 4070 SUPER?▾
The NVIDIA A30 provides 24 GB HBM2 VRAM, double the NVIDIA GeForce RTX 4070 SUPER's 12 GB GDDR6X. This advantage suits large model training. The A30's HBM2 also offers lower latency for data center tasks.
What is the FP32 performance comparison between A30 and RTX 4070 SUPER?▾
The RTX 4070 SUPER delivers 35.5 TFLOPS FP32, exceeding the A30's 10.3 TFLOPS by over three times. This boosts training and inference speeds. FP16 matches these figures on both GPUs.
How do memory bandwidths compare for A30 vs RTX 4070 SUPER?▾
A30 achieves 933 GB/s with HBM2, nearly double the RTX 4070 SUPER's 504 GB/s GDDR6X. Higher bandwidth supports larger batches in ML workloads. It reduces transfer overhead in memory-bound scenarios.
Which GPU consumes less power, A30 or RTX 4070 SUPER?▾
The A30 draws 165 W TDP, lower than the RTX 4070 SUPER's 220 W. This lowers cooling needs in clusters. Efficiency per watt favors RTX 4070 SUPER due to 35.5 TFLOPS versus 10.3 TFLOPS.
Does the A30 or RTX 4070 SUPER support multi-GPU interconnects?▾
The A30 includes NVLink for high-speed multi-GPU communication, absent on the RTX 4070 SUPER. This enables efficient scaling in distributed training. PCIe suffices for both in single-GPU setups.
Which architecture is newer, Ampere in A30 or Ada Lovelace in RTX 4070 SUPER?▾
Ada Lovelace from 2023 powers the RTX 4070 SUPER, succeeding Ampere in 2021 for the A30. Newer design yields 35.5 TFLOPS versus 10.3 TFLOPS. It includes advanced AI and ray-tracing cores.
Which is cheaper to rent, the A30 or the RTX 4070?▾
Cloud rental prices for both the A30 and RTX 4070 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 4070?▾
The A30 has 24 GB of HBM2 memory. The RTX 4070 has 12 GB of GDDR6X memory.
Can I find A30 and RTX 4070 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 4070?▾
The A30 uses the Ampere architecture (2021) while the RTX 4070 uses Ada Lovelace (2023). The RTX 4070 delivers 2.8x the FP16 throughput and 1.9x the memory bandwidth of the A30.