Specifications Compared
| Spec | RTX-2070 | RTX-4070 |
|---|---|---|
| TDP | 175W | 200W |
| VRAM | 8 GB | 12 GB |
| CUDA Cores | 2,304 | 5,888 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Turing | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 288 | 184 |
| FP16 Performance | 7.5 TFLOPS | 29.1 TFLOPS |
| FP32 Performance | 7.5 TFLOPS | 29.1 TFLOPS |
| Memory Bandwidth | 448 GB/s | 504 GB/s |
Performance Analysis
Compute capabilities define the core disparity: the RTX 4070 SUPER achieves 36 TFLOPS in both FP16 and FP32, compared to 9 TFLOPS on the RTX 2070 SUPER. For machine learning, this quadruples training speeds on FP16-precision models and accelerates FP32 scientific simulations, reducing epoch times substantially in deep learning pipelines.
Memory configurations further advantage the newer GPU. With 12 GB GDDR6X versus 8 GB GDDR6, the RTX 4070 SUPER handles larger models and batch sizes without swapping to system RAM, critical for LLM inference or fine-tuning. Its 504 GB/s bandwidth over 448 GB/s minimizes bottlenecks during high-throughput data transfers, enabling larger batches in training runs.
Power draw remains close at 220 W TDP for the RTX 4070 SUPER against 215 W for the RTX 2070 SUPER, yet Ada Lovelace efficiencies yield superior performance per watt. This combination positions the RTX 4070 SUPER for demanding real-time inference, where low latency depends on rapid FP16 tensor operations.
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 RTX 2070 SUPER
The RTX 2070 SUPER fits scenarios constrained by budget or legacy software compatibility, where workloads stay under 8 GB VRAM and 9 TFLOPS FP32 suffices. Light inference tasks or prototyping small neural networks benefit from its 448 GB/s bandwidth without overprovisioning resources.
Cloud users seeking minimal power at 215 W TDP select it for non-intensive scientific computing or older Stable Diffusion models that do not exceed its specs.
When to Choose the RTX 4070 SUPER
Opt for the RTX 4070 SUPER in performance-critical applications demanding 36 TFLOPS FP16 or FP32, such as LLM training or high-resolution Stable Diffusion. Its 12 GB GDDR6X VRAM accommodates complex models that surpass the RTX 2070 SUPER's 8 GB limit.
The 504 GB/s bandwidth excels in large-batch inference, making it ideal for production deployments where speed trumps minor TDP increases to 220 W.
Use Cases
The RTX 4070 SUPER's 12 GB VRAM and 36 TFLOPS FP16 support larger models and batches than the RTX 2070 SUPER's 8 GB and 9 TFLOPS. This accelerates convergence in demanding training runs.
36 TFLOPS FP16 on the RTX 4070 SUPER delivers lower latency for real-time queries compared to 9 TFLOPS on the RTX 2070 SUPER. Higher bandwidth at 504 GB/s aids high-throughput serving.
RTX 4070 SUPER manages fine-tuning of models up to 12 GB with 36 TFLOPS compute, far beyond the RTX 2070 SUPER's 8 GB limit and 9 TFLOPS capacity.
12 GB GDDR6X VRAM on RTX 4070 SUPER enables higher-resolution image generation without issues, paired with 36 TFLOPS for faster iterations over RTX 2070 SUPER's 8 GB setup.
Light FP32 workloads under 9 TFLOPS fit RTX 2070 SUPER adequately, but intensive simulations leverage RTX 4070 SUPER's 36 TFLOPS and extra bandwidth.
Frequently Asked Questions
What is the compute performance difference between RTX 2070 SUPER and RTX 4070 SUPER?▾
The RTX 4070 SUPER provides 36 TFLOPS FP16 and FP32, versus 9 TFLOPS on the RTX 2070 SUPER. This fourfold increase boosts training and inference speeds significantly. Bandwidth also rises to 504 GB/s from 448 GB/s.
Which GPU has more VRAM: RTX 2070 SUPER or RTX 4070 SUPER?▾
RTX 4070 SUPER features 12 GB GDDR6X compared to 8 GB GDDR6 on RTX 2070 SUPER. The extra capacity supports larger AI models and bigger batches. GDDR6X offers higher speeds contributing to 504 GB/s bandwidth.
How do the TDPs compare for RTX 2070 SUPER vs RTX 4070 SUPER?▾
RTX 2070 SUPER consumes 215 W TDP, while RTX 4070 SUPER requires 220 W. The small gap accompanies vastly higher 36 TFLOPS performance on the newer card. Efficiency gains in Ada architecture offset the difference.
Is RTX 4070 SUPER better for machine learning than RTX 2070 SUPER?▾
Yes, RTX 4070 SUPER excels with 36 TFLOPS FP16/FP32 and 12 GB VRAM for ML tasks. RTX 2070 SUPER's 9 TFLOPS and 8 GB limit it to lighter workloads. Bandwidth at 504 GB/s versus 448 GB/s aids data-heavy training.
What architectures do RTX 2070 SUPER and RTX 4070 SUPER use?▾
RTX 2070 SUPER employs Turing from 2018, while RTX 4070 SUPER uses Ada Lovelace from 2023. The five-year gap yields improvements like 36 TFLOPS over 9 TFLOPS. Both support PCIe form factors.
RTX 2070 SUPER vs RTX 4070 SUPER memory bandwidth?▾
RTX 4070 SUPER delivers 504 GB/s, exceeding RTX 2070 SUPER's 448 GB/s by 12.5 percent. This enhances batch processing in inference. Paired with 12 GB VRAM, it outperforms in memory-bound scenarios.
Which is cheaper to rent, the RTX 2070 or the RTX 4070?▾
Cloud rental prices for both the RTX 2070 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 RTX 2070 have compared to the RTX 4070?▾
The RTX 2070 has 8 GB of GDDR6 memory. The RTX 4070 has 12 GB of GDDR6X memory.
Can I find RTX 2070 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 RTX 2070 and the RTX 4070?▾
The RTX 2070 uses the Turing architecture (2018) while the RTX 4070 uses Ada Lovelace (2023). The RTX 4070 delivers 3.9x the FP16 throughput and 1.1x the memory bandwidth of the RTX 2070.