Specifications Compared
| Spec | RTX-4080 | RTX-5070 |
|---|---|---|
| TDP | 320W | 250W |
| VRAM | 16 GB | 12 GB |
| CUDA Cores | 9,728 | 6,144 |
| Memory Type | GDDR6X | GDDR7 |
| Architecture | Ada Lovelace | Blackwell |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 304 | 192 |
| FP16 Performance | 48.7 TFLOPS | 40.6 TFLOPS |
| FP32 Performance | 48.7 TFLOPS | 40.6 TFLOPS |
| INT8 Performance | 780 TOPS | 650 TOPS |
| Memory Bandwidth | 717 GB/s | 448 GB/s |
Performance Analysis
Superior compute on the RTX 4080 SUPER delivers tangible gains: its 48.7 TFLOPS in FP16 and FP32 outperforms the RTX 5070's 40.6 TFLOPS by 20 percent, accelerating AI training and inference where half-precision operations dominate. Equal FP16 and FP32 rates on both indicate strong tensor core support, but the RTX 4080 SUPER's edge shortens epochs in model training by handling more floating-point operations per second.
Memory specifications shape practical limits: 16 GB VRAM on the RTX 4080 SUPER supports larger models than the RTX 5070's 12 GB, while 717 GB/s bandwidth versus 448 GB/s minimizes data transfer bottlenecks. This enables bigger batch sizes in training, reducing overhead and improving throughput in memory-bound scenarios like LLM fine-tuning. The RTX 5070's lower 250W TDP suggests better efficiency per watt, though the RTX 4080 SUPER's 320W sustains higher sustained loads in demanding cloud instances.
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 4080 SUPER
The RTX 4080 SUPER excels in memory-intensive applications requiring 16 GB VRAM, such as training large language models exceeding 12 GB thresholds. Its 717 GB/s bandwidth and 48.7 TFLOPS compute handle substantial batch sizes without throttling, ideal for scientific simulations or high-resolution Stable Diffusion generations where the RTX 5070's 448 GB/s and 12 GB limit scalability.
When to Choose the RTX 5070
Opt for the RTX 5070 in cost-sensitive deployments: its $0.08 per hour starting price and $0.16 average undercut the RTX 4080 SUPER's $0.32 average by 50 percent. The 250W TDP and Blackwell architecture suit efficient inference or lighter fine-tuning, leveraging newer features for power-constrained cloud environments without sacrificing viability for sub-12 GB models.
Use Cases
The RTX 4080 SUPER's 16 GB VRAM and 717 GB/s bandwidth support larger models and batches than the RTX 5070's 12 GB and 448 GB/s. Its 48.7 TFLOPS provides 20 percent more compute for faster epochs.
The RTX 5070's lower $0.16 per hour average suits high-volume inference at scale. Its 40.6 TFLOPS handles sub-12 GB models efficiently with 250W TDP.
48.7 TFLOPS and 16 GB VRAM on the RTX 4080 SUPER accelerate fine-tuning of memory-heavy adapters. Superior bandwidth prevents bottlenecks during iterative updates.
RTX 4080 SUPER's 16 GB VRAM manages high-resolution image batches, with 717 GB/s bandwidth speeding generation over the RTX 5070's limits.
Higher 48.7 TFLOPS FP32 performance excels in simulations requiring dense computations. 320W TDP sustains prolonged scientific workloads.
Frequently Asked Questions
Which GPU has more VRAM: RTX 4080 SUPER or RTX 5070?▾
The RTX 4080 SUPER offers 16 GB GDDR6X VRAM, exceeding the RTX 5070's 12 GB GDDR7. This advantage supports larger AI models and bigger batch sizes in training. Memory bandwidth follows suit at 717 GB/s versus 448 GB/s.
How do the compute performances compare?▾
RTX 4080 SUPER delivers 48.7 TFLOPS in FP16 and FP32, 20 percent above the RTX 5070's 40.6 TFLOPS per precision. This boosts training and inference speeds significantly. Both maintain equal FP16 and FP32 rates for balanced workloads.
What are the cloud pricing differences?▾
RTX 5070 starts at $0.08 per hour averaging $0.16 across two offers, half the RTX 4080 SUPER's $0.17 start and $0.32 average over three. Lower costs favor the RTX 5070 for budget runs. Prices reflect live market data.
Which has lower power consumption?▾
The RTX 5070 uses 250W TDP, less than the RTX 4080 SUPER's 320W. This improves efficiency in power-limited clouds. Newer Blackwell architecture enhances per-watt performance.
What architectures do they use?▾
RTX 4080 SUPER runs Ada Lovelace from 2022, while RTX 5070 uses Blackwell from 2025. Blackwell brings advancements in RT and tensor cores. Specs show RTX 4080 SUPER leading in raw TFLOPS and bandwidth.
Is RTX 5070 better for cost-effective inference?▾
Yes, with $0.16 per hour average and 40.6 TFLOPS for models under 12 GB. It outperforms RTX 4080 SUPER on value despite lower specs. 250W TDP aids sustained low-cost serving.
Which is cheaper to rent, the RTX 4080 or the RTX 5070?▾
Cloud rental prices for both the RTX 4080 and RTX 5070 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 4080 have compared to the RTX 5070?▾
The RTX 4080 has 16 GB of GDDR6X memory. The RTX 5070 has 12 GB of GDDR7 memory.
Can I find RTX 4080 and RTX 5070 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 4080 and the RTX 5070?▾
The RTX 4080 uses the Ada Lovelace architecture (2022) while the RTX 5070 uses Blackwell (2025). The RTX 4080 delivers 1.2x the FP16 throughput and 1.6x the memory bandwidth of the RTX 5070.