Specifications Compared
| Spec | GTX-1080 | QUADRO-RTX-8000 |
|---|---|---|
| TDP | 180W | 260W |
| VRAM | 8-11 GB | 48 GB |
| CUDA Cores | 2,560 | 4,608 |
| Memory Type | GDDR5X | GDDR6 |
| Architecture | Pascal | Turing |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| FP16 Performance | 8.9 TFLOPS | 16.3 TFLOPS |
| FP32 Performance | 8.9 TFLOPS | 16.3 TFLOPS |
| Memory Bandwidth | 320 GB/s | 672 GB/s |
Performance Analysis
The Quadro RTX 8000 outperforms the GTX 1080 in raw compute with 16.3 TFLOPS FP32 versus 8.9 TFLOPS, an 83 percent increase that accelerates matrix operations in training and inference. Both GPUs maintain equal FP16 to FP32 ratios at 1:1, enabling efficient half-precision training without penalties relative to single precision. This benefits deep learning pipelines where FP16 reduces memory usage while sustaining throughput.
Memory capacity presents the largest gap: 48 GB GDDR6 on the Quadro RTX 8000 versus 8 to 11 GB GDDR5X on the GTX 1080 supports vastly larger models and batch sizes in LLM training or Stable Diffusion. Bandwidth at 672 GB/s doubles the GTX 1080's 320 GB/s, minimizing bottlenecks in memory-bound inference tasks and allowing higher throughput for large datasets.
Higher TDP of 260W on the Quadro RTX 8000 reflects its capability for sustained loads, while NVLink enables multi-GPU configurations absent on the GTX 1080. These factors position the Quadro RTX 8000 for professional-scale AI, whereas the GTX 1080 suits lighter, cost-sensitive deployments.
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 |
When to Choose the GTX 1080
The GTX 1080 fits budget-conscious users needing entry-level compute. Its 180W TDP and pricing from $0.30 per hour make it ideal for gaming, light inference, or prototyping on small models under 8 GB VRAM. Availability across two cloud providers ensures quick access without the multi-GPU complexity of NVLink.
Scenarios include hobbyist Stable Diffusion runs or basic scientific simulations where 8.9 TFLOPS FP32 suffices and 320 GB/s bandwidth handles modest batch sizes.
When to Choose the Quadro RTX 8000
The Quadro RTX 8000 excels in professional workflows demanding high VRAM. Its 48 GB GDDR6 capacity supports large-scale LLM training or fine-tuning with batch sizes infeasible on the GTX 1080's 8 to 11 GB. Superior 16.3 TFLOPS FP32 and 672 GB/s bandwidth accelerate memory-intensive tasks like rendering or scientific computing.
NVLink interconnect enables scaled multi-GPU setups for enterprise AI, justifying the 260W TDP in data centers despite current lack of cloud listings.
Use Cases
The Quadro RTX 8000's 48 GB VRAM and 16.3 TFLOPS FP32 support large batch sizes and models infeasible on the GTX 1080's 8 to 11 GB limit. Higher 672 GB/s bandwidth reduces memory bottlenecks during gradient computations.
48 GB GDDR6 enables serving massive LLMs without quantization losses, unlike the GTX 1080's constrained 8 to 11 GB. 16.3 TFLOPS FP16 delivers 83 percent higher throughput for real-time queries.
Quadro RTX 8000's ample VRAM fits adapter layers on billion-parameter models, with NVLink for multi-GPU efficiency. GTX 1080 struggles with batches exceeding 8 GB.
48 GB VRAM accommodates high-resolution generations and LoRA training, leveraging 672 GB/s bandwidth for faster sampling. GTX 1080 limits to smaller images due to 320 GB/s and low capacity.
GTX 1080 suffices for modest simulations at 8.9 TFLOPS and $0.30 per hour. Quadro RTX 8000 scales to complex datasets with 48 GB VRAM and NVLink.
Frequently Asked Questions
What is the VRAM difference between GTX 1080 and Quadro RTX 8000?▾
The GTX 1080 offers 8 to 11 GB GDDR5X VRAM. The Quadro RTX 8000 provides 48 GB GDDR6 VRAM, enabling larger models and batch sizes in AI tasks.
How do FP32 performance levels compare?▾
GTX 1080 achieves 8.9 TFLOPS FP32. Quadro RTX 8000 reaches 16.3 TFLOPS FP32, an 83 percent improvement for training and simulations.
What are the current cloud prices for these GPUs?▾
GTX 1080 rentals start at $0.30 per hour, averaging $0.45 per hour across two offers. Quadro RTX 8000 has no live cloud offers available.
Does Quadro RTX 8000 support multi-GPU setups better?▾
Quadro RTX 8000 includes NVLink interconnect for efficient scaling. GTX 1080 lacks specified interconnect beyond PCIe.
Which has higher memory bandwidth?▾
Quadro RTX 8000 delivers 672 GB/s bandwidth. GTX 1080 provides 320 GB/s, doubling potential throughput for memory-bound workloads.
What are the TDP ratings?▾
GTX 1080 consumes 180W. Quadro RTX 8000 requires 260W, reflecting its higher performance capabilities.
Which is cheaper to rent, the GTX 1080 or the Quadro RTX 8000?▾
Cloud rental prices for both the GTX 1080 and Quadro RTX 8000 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 Quadro RTX 8000?▾
The GTX 1080 has 8 to 11 GB of GDDR5X memory. The Quadro RTX 8000 has 48 GB of GDDR6 memory.
Can I find GTX 1080 and Quadro RTX 8000 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 Quadro RTX 8000?▾
The GTX 1080 uses the Pascal architecture (2016) while the Quadro RTX 8000 uses Turing (2018). The Quadro RTX 8000 delivers 1.8x the FP16 throughput and 2.1x the memory bandwidth of the GTX 1080.