Specifications Compared
| Spec | RTX-4080 | RTX-5000-ADA |
|---|---|---|
| TDP | 320W | 250W |
| VRAM | 16 GB | 32 GB |
| CUDA Cores | 9,728 | 12,800 |
| Memory Type | GDDR6X | GDDR6 |
| Architecture | Ada Lovelace | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 304 | 400 |
| FP16 Performance | 48.7 TFLOPS | 65.3 TFLOPS |
| FP32 Performance | 48.7 TFLOPS | 65.3 TFLOPS |
| INT8 Performance | 780 TOPS | 1,044 TOPS |
| Memory Bandwidth | 717 GB/s | 576 GB/s |
Performance Analysis
Compute performance favors the RTX 5000 Ada Generation: it achieves 65.3 TFLOPS in both FP16 and FP32, a 34 percent increase over the RTX 4080 SUPER's 48.7 TFLOPS. This delta accelerates neural network training and inference, reducing epochs needed for convergence in deep learning pipelines.
VRAM capacity defines workload scalability: 32 GB on the RTX 5000 Ada Generation supports larger batch sizes for LLMs exceeding 16 GB limits on the RTX 4080 SUPER, minimizing out-of-memory errors. However, the RTX 4080 SUPER's 717 GB/s bandwidth outperforms the 576 GB/s of the RTX 5000 Ada Generation, enhancing data transfer in bandwidth-bound scenarios like high-resolution image generation.
Efficiency edges to the RTX 5000 Ada Generation with a 250 W TDP versus 320 W on the RTX 4080 SUPER, lowering energy costs for extended cloud sessions.
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 |
RTX 5000 Ada Generation
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA RTX 5000 Ada Generation 32GB VRAM | 32GB | 0 vCPU 0GB RAM | Chubbuck, Idaho | $0.55/GPU/hr | Available | ||
RunPod | NVIDIA RTX 5000 Ada Generation 32GB VRAM | 32GB | 10 vCPU 83GB RAM | 🌍global | $0.83/GPU/hr |
When to Choose the RTX 4080 SUPER
Select the RTX 4080 SUPER for budget-conscious projects requiring high memory bandwidth. Its 717 GB/s rate excels in Stable Diffusion tasks or inference with models under 16 GB VRAM, where faster data access boosts throughput. Starting at $0.17 per hour, it delivers strong value across three cloud offers averaging $0.32 per hour.
When to Choose the RTX 5000 Ada Generation
The RTX 5000 Ada Generation suits memory-demanding workloads like large LLM training. 32 GB VRAM enables handling models that exceed the RTX 4080 SUPER's 16 GB capacity, paired with 65.3 TFLOPS for superior speed. Despite averaging $0.51 per hour, its efficiency at 250 W TDP justifies selection for professional pipelines.
Use Cases
The RTX 5000 Ada Generation's 32 GB VRAM accommodates massive models, preventing memory constraints during training. Its 65.3 TFLOPS exceeds the RTX 4080 SUPER's 48.7 TFLOPS for quicker convergence.
32 GB VRAM on the RTX 5000 Ada Generation supports high-concurrency inference for large LLMs. Higher 65.3 TFLOPS ensures lower latency compared to the 16 GB RTX 4080 SUPER.
Fine-tuning often fits within 16 GB VRAM of the RTX 4080 SUPER, leveraging its 717 GB/s bandwidth. RTX 5000 Ada Generation's 32 GB aids larger datasets.
RTX 4080 SUPER's 717 GB/s bandwidth accelerates texture loading and generation. Lower $0.17 per hour pricing suits iterative creative workflows.
65.3 TFLOPS FP32 performance on RTX 5000 Ada Generation speeds simulations. 32 GB VRAM handles complex datasets beyond RTX 4080 SUPER limits.
Frequently Asked Questions
Which GPU has more VRAM: RTX 4080 SUPER or RTX 5000 Ada Generation?▾
The RTX 5000 Ada Generation offers 32 GB GDDR6 VRAM, double the 16 GB GDDR6X of the RTX 4080 SUPER. This enables larger models in AI tasks. Bandwidth remains higher on RTX 4080 SUPER at 717 GB/s versus 576 GB/s.
What is the performance difference in TFLOPS?▾
RTX 5000 Ada Generation delivers 65.3 TFLOPS in FP16 and FP32, outperforming RTX 4080 SUPER's 48.7 TFLOPS by 34 percent. This impacts training and inference speeds. Both share Ada Lovelace architecture.
How do cloud prices compare?▾
RTX 4080 SUPER starts at $0.17 per hour, averaging $0.32 per hour across three offers. RTX 5000 Ada Generation begins at $0.25 per hour, averaging $0.51 per hour over five offers. Pricing reflects VRAM and compute differences.
Which has lower power consumption?▾
RTX 5000 Ada Generation uses 250 W TDP, lower than RTX 4080 SUPER's 320 W. This improves efficiency in cloud environments. Lower TDP reduces cooling needs.
Is RTX 5000 Ada better for large models?▾
Yes, 32 GB VRAM on RTX 5000 Ada Generation supports LLMs over 16 GB threshold of RTX 4080 SUPER. 65.3 TFLOPS further accelerates processing. Bandwidth edge goes to RTX 4080 SUPER at 717 GB/s.
Are both GPUs PCIe compatible?▾
Both RTX 4080 SUPER and RTX 5000 Ada Generation use PCIe form factors with no interconnect specified. They suit standard cloud instances. VRAM and TDP differentiate deployment.
Which is cheaper to rent, the RTX 4080 or the RTX 5000 Ada?▾
Cloud rental prices for both the RTX 4080 and RTX 5000 Ada 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 5000 Ada?▾
The RTX 4080 has 16 GB of GDDR6X memory. The RTX 5000 Ada has 32 GB of GDDR6 memory.
Can I find RTX 4080 and RTX 5000 Ada 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 5000 Ada?▾
The RTX 4080 uses the Ada Lovelace architecture (2022) while the RTX 5000 Ada uses Ada Lovelace (2023). The RTX 5000 Ada delivers 1.3x the FP16 throughput and 1.2x the memory bandwidth of the RTX 4080.