Specifications Compared
| Spec | GTX-1080 | RTX-3090 |
|---|---|---|
| TDP | 180W | 350W |
| VRAM | 8-11 GB | 24 GB |
| CUDA Cores | 2,560 | 10,496 |
| Memory Type | GDDR5X | GDDR6X |
| Architecture | Pascal | Ampere |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| FP16 Performance | 8.9 TFLOPS | 35.6 TFLOPS |
| FP32 Performance | 8.9 TFLOPS | 35.6 TFLOPS |
| Memory Bandwidth | 320 GB/s | 936 GB/s |
Performance Analysis
RTX 3090 Ti demonstrates superior compute performance over GTX 1080: 35.6 TFLOPS FP16 and FP32 versus 8.9 TFLOPS, enabling approximately four times faster matrix operations critical for neural network training and inference. This FP16 and FP32 parity on each GPU simplifies mixed-precision workflows, but RTX 3090 Ti's scale handles complex models efficiently.
Memory capacity and speed profoundly impact real-world usage. RTX 3090 Ti's 24 GB VRAM accommodates larger batch sizes and models than GTX 1080's 8 to 11 GB, reducing out-of-memory errors in deep learning. The 936 GB/s bandwidth versus 320 GB/s minimizes data transfer bottlenecks, supporting higher throughput in data-intensive tasks like image generation or simulations.
Power and form factors influence deployment: both use PCIe, but RTX 3090 Ti's 350W TDP demands stronger infrastructure compared to GTX 1080's 180W.
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 3090 Ti
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 0 vCPU 0GB RAM | Wilmington, Delaware | $0.20/GPU/hr | Available | ||
TensorDock | NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 0 vCPU 0GB RAM | Dallas, Texas | $0.21/GPU/hr | Available | ||
 Vast.ai | 4×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 32 vCPU 403GB RAM 104GB Storage | Iceland | $0.25/GPU/hr $1.01/hr total (4×) | Available | ||
Vast.ai | 4×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 32 vCPU 252GB RAM 1217GB Storage | Finland | $0.27/GPU/hr $1.07/hr total (4×) | Available | ||
LeaderGPU | 8×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.29/GPU/hr $2.29/hr total (8×) | Available |
When to Choose the GTX 1080
GTX 1080 fits scenarios with light computational demands where 8.9 TFLOPS FP32 performance suffices for basic inference or legacy software. Its 180W TDP enables use in power-constrained cloud instances or desktops, and $0.30 per hour pricing avoids excess cost for models under 8 GB VRAM.
When to Choose the RTX 3090 Ti
RTX 3090 Ti serves demanding AI and graphics workloads requiring 24 GB VRAM and 936 GB/s bandwidth for large batches. NVLink interconnect aids multi-GPU setups, and 35.6 TFLOPS FP16 accelerates training; average $0.25 per hour pricing delivers strong value across five offers.
Use Cases
RTX 3090 Ti's 24 GB VRAM and 35.6 TFLOPS FP16 support large language models that exceed GTX 1080's 8 to 11 GB capacity.
35.6 TFLOPS FP32 on RTX 3090 Ti enables low-latency inference on bigger models; GTX 1080 limits scale with 8.9 TFLOPS and lower VRAM.
RTX 3090 Ti's 936 GB/s bandwidth handles large datasets during fine-tuning, outperforming GTX 1080's 320 GB/s for efficient iterations.
24 GB VRAM on RTX 3090 Ti fits high-resolution Stable Diffusion generations without swapping, unlike GTX 1080's 8 to 11 GB constraint.
RTX 3090 Ti's NVLink and 35.6 TFLOPS accelerate parallel simulations; GTX 1080 lacks interconnect and trails in compute density.
Frequently Asked Questions
Which GPU has more VRAM: GTX 1080 or RTX 3090 Ti?▾
RTX 3090 Ti provides 24 GB GDDR6X VRAM, surpassing GTX 1080's 8 to 11 GB GDDR5X. This enables larger models in AI tasks. Bandwidth also favors RTX 3090 Ti at 936 GB/s over 320 GB/s.
What is the performance difference in TFLOPS?▾
RTX 3090 Ti achieves 35.6 TFLOPS in FP16 and FP32, about four times GTX 1080's 8.9 TFLOPS per precision. This boosts training speeds significantly. Real-world ML benchmarks reflect this gap.
How do cloud prices compare for these GPUs?▾
GTX 1080 rents from $0.30 per hour averaging $0.30 across one offer. RTX 3090 Ti starts at $0.10 per hour, averaging $0.25 over five offers. RTX 3090 Ti often provides better value.
What are the TDP ratings?▾
GTX 1080 consumes 180W TDP, suitable for modest power setups. RTX 3090 Ti requires 350W, needing robust cooling. Both fit PCIe form factors.
Does RTX 3090 Ti support NVLink?▾
RTX 3090 Ti includes NVLink interconnect for multi-GPU scaling. GTX 1080 lacks this feature. NVLink enhances bandwidth in clustered workloads.
Which is better for machine learning training?▾
RTX 3090 Ti excels with 35.6 TFLOPS FP16 and 24 GB VRAM for large batches. GTX 1080's 8.9 TFLOPS and 8 to 11 GB limit it to smaller models.
Which is cheaper to rent, the GTX 1080 or the RTX 3090?▾
Cloud rental prices for both the GTX 1080 and RTX 3090 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 3090?▾
The GTX 1080 has 8 to 11 GB of GDDR5X memory. The RTX 3090 has 24 GB of GDDR6X memory.
Can I find GTX 1080 and RTX 3090 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 3090?▾
The GTX 1080 uses the Pascal architecture (2016) while the RTX 3090 uses Ampere (2020). The RTX 3090 delivers 4.0x the FP16 throughput and 2.9x the memory bandwidth of the GTX 1080.