Specifications Compared
| Spec | RTX-2070 | RTX-4080 |
|---|---|---|
| TDP | 175W | 320W |
| VRAM | 8 GB | 16 GB |
| CUDA Cores | 2,304 | 9,728 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Turing | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 288 | 304 |
| FP16 Performance | 7.5 TFLOPS | 48.7 TFLOPS |
| FP32 Performance | 7.5 TFLOPS | 48.7 TFLOPS |
| Memory Bandwidth | 448 GB/s | 717 GB/s |
Performance Analysis
Compute performance differs dramatically between these GPUs: the RTX 4080 SUPER achieves 52 TFLOPS in FP16 and FP32, compared to 9.1 TFLOPS on the RTX 2070 SUPER, yielding roughly 5.7 times faster processing for training neural networks. This delta accelerates deep learning training epochs and enables handling larger models without proportional time increases. For inference, the higher FP16 throughput on the 4080 SUPER supports more concurrent queries in production deployments. Memory bandwidth presents another key disparity: 736 GB/s on the 4080 SUPER versus 448 GB/s on the 2070 SUPER permits larger batch sizes in memory-intensive workloads like LLM fine-tuning, reducing bottlenecks and improving throughput by up to 64 percent. The 4080 SUPER's 16 GB VRAM doubles the 2070 SUPER's 8 GB capacity, sustaining bigger datasets during scientific simulations or diffusion model generation. Power draw reflects this: 320 W TDP for the 4080 SUPER versus 215 W for the 2070 SUPER demands robust cooling but delivers proportional gains.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 4080 SUPER
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4080 SUPER 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr | |||
RunPod | NVIDIA GeForce RTX 4080 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the RTX 2070 SUPER
The RTX 2070 SUPER suits legacy applications optimized for Turing architecture, such as older game engines or basic ML inference with models under 8 GB VRAM. Its 215 W TDP fits power-limited desktops or laptops without high electricity costs. Absence of cloud offers makes it preferable for on-premises hardware already owned, avoiding rental expenses for light workloads like 1080p rendering.
When to Choose the RTX 4080 SUPER
Opt for the RTX 4080 SUPER in modern AI pipelines requiring 52 TFLOPS compute and 16 GB VRAM for large LLMs or high-resolution Stable Diffusion. Cloud availability at $0.17 per hour enables scalable training without upfront hardware investment. Superior 736 GB/s bandwidth handles demanding batch processing in fine-tuning or scientific computing.
Use Cases
RTX 4080 SUPER's 52 TFLOPS FP32 and 16 GB VRAM handle large models efficiently, unlike RTX 2070 SUPER's 9.1 TFLOPS and 8 GB limits.
Higher 736 GB/s bandwidth on RTX 4080 SUPER supports bigger batches for faster serving; 2070 SUPER's 448 GB/s bottlenecks at scale.
52 TFLOPS FP16 on RTX 4080 SUPER speeds iterations on mid-size models; 2070 SUPER's 9.1 TFLOPS prolongs sessions unnecessarily.
16 GB VRAM and 52 TFLOPS enable high-res generations quickly on RTX 4080 SUPER; 8 GB on 2070 SUPER restricts image sizes.
RTX 4080 SUPER's 736 GB/s bandwidth and doubled VRAM accelerate simulations; 2070 SUPER suffices only for small datasets.
Frequently Asked Questions
What is the compute performance difference between RTX 2070 SUPER and RTX 4080 SUPER?▾
The RTX 4080 SUPER delivers 52 TFLOPS in FP16 and FP32, while the RTX 2070 SUPER provides 9.1 TFLOPS in both. This results in approximately 5.7 times faster processing for AI tasks. Higher performance scales to complex workloads effectively.
How much VRAM do RTX 2070 SUPER and RTX 4080 SUPER have?▾
RTX 2070 SUPER features 8 GB GDDR6 VRAM, sufficient for smaller models. RTX 4080 SUPER offers 16 GB GDDR6X, doubling capacity for large LLMs. The extra VRAM prevents out-of-memory errors in training.
Is RTX 2070 SUPER available on cloud GPU rentals?▾
No live cloud offers exist for RTX 2070 SUPER currently. RTX 4080 SUPER provides options from $0.17 per hour, averaging $0.32 per hour across three providers. Cloud access favors the newer GPU for flexible scaling.
What are the power requirements for these GPUs?▾
RTX 2070 SUPER has a 215 W TDP, suitable for modest power supplies. RTX 4080 SUPER requires 320 W, needing stronger PSUs and cooling. Higher TDP correlates with its superior 52 TFLOPS performance.
Which GPU has higher memory bandwidth?▾
RTX 4080 SUPER achieves 736 GB/s bandwidth with GDDR6X memory. RTX 2070 SUPER offers 448 GB/s with GDDR6. The gap improves batch sizes in inference by up to 64 percent.
Can RTX 2070 SUPER handle modern AI training?▾
RTX 2070 SUPER's 9.1 TFLOPS and 8 GB VRAM limit it to small models or basic fine-tuning. Larger tasks exceed its capacity quickly. RTX 4080 SUPER's specs make it far more capable.
Which is cheaper to rent, the RTX 2070 or the RTX 4080?▾
Cloud rental prices for both the RTX 2070 and RTX 4080 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 4080?▾
The RTX 2070 has 8 GB of GDDR6 memory. The RTX 4080 has 16 GB of GDDR6X memory.
Can I find RTX 2070 and RTX 4080 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 4080?▾
The RTX 2070 uses the Turing architecture (2018) while the RTX 4080 uses Ada Lovelace (2022). The RTX 4080 delivers 6.5x the FP16 throughput and 1.6x the memory bandwidth of the RTX 2070.