Specifications Compared
| Spec | RTX-3070 | RTX-4080 |
|---|---|---|
| TDP | 220W | 320W |
| VRAM | 8 GB | 16 GB |
| CUDA Cores | 5,888 | 9,728 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 184 | 304 |
| FP16 Performance | 20.3 TFLOPS | 48.7 TFLOPS |
| FP32 Performance | 20.3 TFLOPS | 48.7 TFLOPS |
| Memory Bandwidth | 448 GB/s | 717 GB/s |
Performance Analysis
The RTX 4080 SUPER outperforms the RTX 3070 by more than double in raw compute: 48.7 TFLOPS FP16 and FP32 versus 20.3 TFLOPS. This translates to approximately 2.4 times faster theoretical performance for machine learning workloads, including training and inference where half-precision FP16 dominates. Training large models benefits directly, as the higher throughput reduces epoch times significantly.
Memory specifications create practical limits: the RTX 3070's 8 GB GDDR6 restricts batch sizes for models exceeding this capacity, often requiring gradient accumulation or smaller models. The RTX 4080 SUPER's 16 GB GDDR6X and 717 GB/s bandwidth versus 448 GB/s enable larger batches and faster data movement, minimizing bottlenecks in inference pipelines handling high-resolution inputs or multi-modal data.
Power efficiency varies with TDP: the RTX 3070's 220W suits lighter deployments, while the RTX 4080 SUPER's 320W demands robust cooling but delivers superior perf-per-watt in compute-intensive scenarios due to architectural advances in Ada Lovelace.
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 3070
The RTX 3070 excels in budget-conscious scenarios with light workloads. Its 8 GB VRAM suffices for fine-tuning small language models or running Stable Diffusion at 512x512 resolutions, where full 16 GB proves unnecessary. At $0.04/hr starting price and 220W TDP, it minimizes costs and power for prototyping or inference on models under 7B parameters.
Cloud users prioritizing affordability over peak performance select the RTX 3070, especially with 20.3 TFLOPS handling entry-level scientific computing or gaming benchmarks efficiently across 4 live offers averaging $0.09/hr.
When to Choose the RTX 4080 SUPER
The RTX 4080 SUPER dominates demanding applications requiring ample memory and speed. Its 16 GB VRAM supports training or inferring large language models up to 70B parameters, while 717 GB/s bandwidth accelerates high-batch inference. Users benefit from 48.7 TFLOPS for rapid Stable Diffusion generations at 1024x1024 or complex scientific simulations.
For production-scale ML where performance justifies higher costs, the RTX 4080 SUPER prevails despite $0.17/hr starting and 320W TDP, offering future-proofing via Ada Lovelace across 3 offers averaging $0.32/hr.
Use Cases
The RTX 4080 SUPER's 16 GB VRAM and 48.7 TFLOPS FP16 handle large models and batches better than the RTX 3070's 8 GB limit. Higher 717 GB/s bandwidth reduces training time significantly.
48.7 TFLOPS and 16 GB VRAM on RTX 4080 SUPER support high-throughput serving of 70B models. RTX 3070's 8 GB VRAM constrains concurrent requests.
RTX 3070's 20.3 TFLOPS and 8 GB suffice for small models under 7B parameters at low cost. RTX 4080 SUPER accelerates larger fine-tunes with 16 GB VRAM.
RTX 4080 SUPER generates higher resolutions faster via 48.7 TFLOPS and 717 GB/s bandwidth. RTX 3070 limits to basic 512x512 due to 8 GB VRAM.
48.7 TFLOPS FP32 on RTX 4080 SUPER speeds simulations with large datasets. RTX 3070's 20.3 TFLOPS fits modest workloads but bottlenecks on memory-intensive tasks.
Frequently Asked Questions
Which GPU has more VRAM?▾
The RTX 4080 SUPER provides 16 GB GDDR6X VRAM, double the RTX 3070's 8 GB GDDR6. This allows larger models and batch sizes in ML tasks. Memory bandwidth follows suit at 717 GB/s versus 448 GB/s.
What is the compute performance difference?▾
RTX 4080 SUPER delivers 48.7 TFLOPS in FP16 and FP32, over 2.4 times the RTX 3070's 20.3 TFLOPS per precision. This boosts training and inference speeds substantially. Both maintain equal FP16 and FP32 rates.
How do cloud prices compare?▾
RTX 3070 rentals start at $0.04/hr averaging $0.09/hr across 4 offers. RTX 4080 SUPER begins at $0.17/hr with $0.32/hr average over 3 offers. Cost scales with performance gains.
What are the TDP ratings?▾
The RTX 3070 has a 220W TDP, lower than the RTX 4080 SUPER's 320W. This makes RTX 3070 more power-efficient for light loads. Both use PCIe form factors.
Which architecture is newer?▾
RTX 4080 SUPER uses Ada Lovelace from 2022, succeeding the RTX 3070's Ampere of 2020. Architectural improvements yield higher efficiency. Compute doubles from 20.3 to 48.7 TFLOPS.
Can both handle machine learning?▾
Yes, both support ML with FP16/FP32 performance: 20.3 TFLOPS on RTX 3070 and 48.7 TFLOPS on RTX 4080 SUPER. RTX 4080 SUPER excels in memory-heavy tasks due to 16 GB VRAM.
Which is cheaper to rent, the RTX 3070 or the RTX 4080?▾
Cloud rental prices for both the RTX 3070 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 3070 have compared to the RTX 4080?▾
The RTX 3070 has 8 GB of GDDR6 memory. The RTX 4080 has 16 GB of GDDR6X memory.
Can I find RTX 3070 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 3070 and the RTX 4080?▾
The RTX 3070 uses the Ampere architecture (2020) while the RTX 4080 uses Ada Lovelace (2022). The RTX 4080 delivers 2.4x the FP16 throughput and 1.6x the memory bandwidth of the RTX 3070.