Specifications Compared
| Spec | GTX-1080 | RTX-4070 |
|---|---|---|
| TDP | 180W | 200W |
| VRAM | 8-11 GB | 12 GB |
| CUDA Cores | 2,560 | 5,888 |
| Memory Type | GDDR5X | GDDR6X |
| Architecture | Pascal | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| FP16 Performance | 8.9 TFLOPS | 29.1 TFLOPS |
| FP32 Performance | 8.9 TFLOPS | 29.1 TFLOPS |
| Memory Bandwidth | 320 GB/s | 504 GB/s |
Performance Analysis
Compute capabilities define the core disparity: the RTX 4070 SUPER's 35.5 TFLOPS in FP16 and FP32 quadruples the GTX 1080's 8.9 TFLOPS, enabling four times faster training and inference for deep learning models. This delta translates to reduced epoch times in LLM training and higher throughput in inference serving, where FP16 precision dominates modern workflows.
Memory bandwidth impacts practical workloads significantly: the RTX 4070 SUPER's 504 GB/s supports larger batch sizes than the GTX 1080's 320 GB/s, minimizing out-of-memory errors during fine-tuning or Stable Diffusion generation with high-resolution inputs. The 12 GB GDDR6X VRAM on the RTX 4070 SUPER handles bigger models compared to the GTX 1080's 8 to 11 GB GDDR5X, enhancing scalability in memory-intensive scientific computing.
Efficiency gains from Ada Lovelace architecture compound these advantages, despite the TDP increase from 180 W to 220 W, yielding superior performance per watt for sustained cloud tasks.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
GTX 1080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 LeaderGPU | 4×NVIDIA GeForce GTX 1080 8GB VRAM | 8GB | 0 vCPU 64GB RAM 480GB Storage | Netherlands | $0.30/GPU/hr $1.20/hr total (4×) | Available | ||
LeaderGPU | 8×NVIDIA GeForce GTX 1080 Ti 11GB VRAM | 11GB | 0 vCPU 128GB RAM 480GB Storage | Netherlands | $0.60/GPU/hr $4.80/hr total (8×) | Available |
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 GTX 1080
The GTX 1080 suits budget-constrained users needing immediate cloud access at $0.30 per hour. Its 180 W TDP fits low-power environments, and 8.9 TFLOPS suffices for lightweight inference or legacy applications where 8 to 11 GB VRAM meets demands without excess cost.
When to Choose the RTX 4070 SUPER
Opt for the RTX 4070 SUPER in performance-critical scenarios leveraging 35.5 TFLOPS FP16/FP32 and 504 GB/s bandwidth for rapid LLM training or high-batch Stable Diffusion. Its 12 GB GDDR6X excels in modern Ada Lovelace-optimized software, ideal for on-premises setups given absent cloud pricing.
Use Cases
The RTX 4070 SUPER's 35.5 TFLOPS FP16 outperforms the GTX 1080's 8.9 TFLOPS, accelerating large model training. Higher 504 GB/s bandwidth supports bigger batches.
RTX 4070 SUPER achieves 35.5 TFLOPS FP32 for faster query throughput than GTX 1080's 8.9 TFLOPS. 12 GB VRAM handles larger models efficiently.
35.5 TFLOPS and 504 GB/s on RTX 4070 SUPER reduce fine-tuning times compared to GTX 1080's specs. Ada architecture optimizes modern frameworks.
RTX 4070 SUPER's 12 GB VRAM and 504 GB/s bandwidth enable high-resolution generations without limits seen on GTX 1080's 8-11 GB and 320 GB/s.
GTX 1080 suffices at $0.30/hr for basic simulations with 8.9 TFLOPS. RTX 4070 SUPER excels in complex tasks needing 35.5 TFLOPS.
Frequently Asked Questions
Which GPU has more VRAM?▾
The RTX 4070 SUPER provides 12 GB GDDR6X, exceeding the GTX 1080's 8 to 11 GB GDDR5X. This supports larger models in AI workloads.
What is the performance difference in TFLOPS?▾
RTX 4070 SUPER delivers 35.5 TFLOPS in FP16 and FP32, versus GTX 1080's 8.9 TFLOPS. This yields approximately four times the compute power.
How does memory bandwidth compare?▾
RTX 4070 SUPER offers 504 GB/s, surpassing GTX 1080's 320 GB/s. Higher bandwidth improves batch sizes in training.
What are the cloud prices?▾
GTX 1080 starts at $0.30 per hour average across offers. RTX 4070 SUPER has no live cloud offers currently.
Which has lower power consumption?▾
GTX 1080 uses 180 W TDP, lower than RTX 4070 SUPER's 220 W. This favors energy-sensitive deployments.
Is RTX 4070 SUPER better for machine learning?▾
Yes, its Ada Lovelace architecture, 35.5 TFLOPS, and 12 GB VRAM outperform GTX 1080's Pascal specs for ML tasks.
Which is cheaper to rent, the GTX 1080 or the RTX 4070?▾
Cloud rental prices for both the GTX 1080 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 GTX 1080 have compared to the RTX 4070?▾
The GTX 1080 has 8 to 11 GB of GDDR5X memory. The RTX 4070 has 12 GB of GDDR6X memory.
Can I find GTX 1080 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 GTX 1080 and the RTX 4070?▾
The GTX 1080 uses the Pascal architecture (2016) while the RTX 4070 uses Ada Lovelace (2023). The RTX 4070 delivers 3.3x the FP16 throughput and 1.6x the memory bandwidth of the GTX 1080.