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
Compute performance reveals a clear leader: the RTX 4080 SUPER delivers 48.7 TFLOPS in FP16 and FP32, exceeding the RTX 3070 Ti's 20.3 TFLOPS by 2.4 times. In machine learning, FP16 enables rapid training of neural networks with minimal accuracy loss, while FP32 supports precise inference and simulations; this delta shortens training epochs and boosts throughput in cloud pipelines. Memory differences impact scalability: 717 GB/s bandwidth and 16 GB VRAM on the RTX 4080 SUPER handle larger batch sizes for models like 13B LLMs, avoiding out-of-memory errors common with the RTX 3070 Ti's 448 GB/s and 8 GB limit. Higher bandwidth reduces data bottlenecks during gradient updates, enhancing overall utilization. The 320W TDP of the RTX 4080 SUPER versus 220W reflects greater capability, though Ada Lovelace optimizations yield better performance per watt in sustained FP16 tasks.
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 Ti
The RTX 3070 Ti excels in cost-constrained environments. With cloud pricing from $0.06 per hour and an average of $0.08 per hour, it powers lightweight inference and fine-tuning for models fitting within 8 GB VRAM at 20.3 TFLOPS. Prototypers and small teams favor it for quick Stable Diffusion generations or scientific computing on modest datasets, where 448 GB/s bandwidth suffices without overspending.
When to Choose the RTX 4080 SUPER
The RTX 4080 SUPER dominates demanding workloads. Its 16 GB GDDR6X VRAM and 717 GB/s bandwidth support large-scale LLM training and high-resolution Stable Diffusion, backed by 48.7 TFLOPS for 2.4 times faster execution than the RTX 3070 Ti. Users prioritize it despite $0.17 per hour starting costs when batch sizes exceed 8 GB limits or speed trumps budget.
Use Cases
The RTX 4080 SUPER's 16 GB VRAM and 717 GB/s bandwidth accommodate larger models and batch sizes critical for efficient LLM training. Its 48.7 TFLOPS FP16 performance accelerates convergence 2.4 times over the RTX 3070 Ti.
RTX 4080 SUPER handles high-throughput inference for 7B-plus parameter LLMs with 16 GB VRAM, avoiding swaps. 48.7 TFLOPS FP16 yields lower latency than the 20.3 TFLOPS and 8 GB limit of RTX 3070 Ti.
RTX 3070 Ti suffices for small datasets under 8 GB at $0.06 per hour. RTX 4080 SUPER excels for larger adapters with 717 GB/s bandwidth boosting batch efficiency.
RTX 4080 SUPER generates higher-resolution images faster via 16 GB VRAM and 48.7 TFLOPS. RTX 3070 Ti limits to 512x512 outputs effectively with 8 GB.
RTX 3070 Ti's 20.3 TFLOPS FP32 and $0.08 per hour average suit simulations fitting 8 GB VRAM. Bandwidth of 448 GB/s handles most array operations adequately.
Frequently Asked Questions
What is the TFLOPS difference between RTX 3070 Ti and RTX 4080 SUPER?▾
The RTX 4080 SUPER provides 48.7 TFLOPS in FP16 and FP32, compared to 20.3 TFLOPS on the RTX 3070 Ti. This 2.4 times increase speeds up AI training and inference significantly. Both maintain equal FP16 and FP32 rates for balanced workloads.
How much VRAM do RTX 3070 Ti and RTX 4080 SUPER have?▾
RTX 3070 Ti offers 8 GB GDDR6 VRAM, suitable for models up to 7B parameters. RTX 4080 SUPER doubles that to 16 GB GDDR6X, enabling larger LLMs without offloading. This affects batch sizes in training.
What are the cloud rental prices for these GPUs?▾
RTX 3070 Ti starts at $0.06 per hour with $0.08 average across two providers. RTX 4080 SUPER begins at $0.17 per hour, averaging $0.32 across three offers. Prices reflect performance scaling.
Which GPU has higher memory bandwidth?▾
RTX 4080 SUPER achieves 717 GB/s, surpassing RTX 3070 Ti's 448 GB/s by 60 percent. Higher bandwidth supports bigger batches in ML training. This reduces data transfer bottlenecks.
Is RTX 3070 Ti sufficient for Stable Diffusion?▾
Yes, RTX 3070 Ti runs Stable Diffusion at 20.3 TFLOPS with 8 GB VRAM for standard 512x512 images. It handles inference well at low cost. Larger tasks benefit from RTX 4080 SUPER.
What are the TDP ratings?▾
RTX 3070 Ti consumes 220W TDP, lower than RTX 4080 SUPER's 320W. Lower power aids budget hosting. Ada architecture improves efficiency per watt.
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.