Specifications Compared
| Spec | RTX-4000-ADA | RTX-5080 |
|---|---|---|
| TDP | 130W | 360W |
| VRAM | 20 GB | 16 GB |
| CUDA Cores | 6,144 | 10,752 |
| Memory Type | GDDR6 | GDDR7 |
| Architecture | Ada Lovelace | Blackwell |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 192 | 336 |
| FP16 Performance | 26.7 TFLOPS | 56.3 TFLOPS |
| FP32 Performance | 26.7 TFLOPS | 56.3 TFLOPS |
| INT8 Performance | 427 TOPS | 900 TOPS |
| Memory Bandwidth | 360 GB/s | 960 GB/s |
Performance Analysis
The RTX 5080 outperforms the RTX 4000 Ada in compute: 56.3 TFLOPS for FP16 and FP32 versus 26.7 TFLOPS represents a 111 percent increase. This advantage accelerates deep learning training, where FP16 mixed precision reduces memory usage while maintaining speed, and FP32 ensures numerical stability in inference. Training large models completes faster on the RTX 5080, potentially halving iteration times.
Memory bandwidth triples from 360 GB/s to 960 GB/s on the RTX 5080, allowing larger batch sizes without stalling data transfers. In training, this sustains higher utilization; for inference, it supports more concurrent requests. The RTX 4000 Ada's 20 GB VRAM exceeds the RTX 5080's 16 GB, aiding single-model loads, but bandwidth limitations cap scalability.
Power draw reflects capabilities: 360W TDP on the RTX 5080 demands robust cooling versus 130W on the RTX 4000 Ada, influencing cloud instance selection for density.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 4000 Ada
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 8 vCPU 50GB RAM | 🌍global | $0.26/GPU/hr | |||
 Vast.ai | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 64 vCPU 42GB RAM 505GB Storage | Hungary | $0.40/GPU/hr | Available | ||
RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 8 vCPU 50GB RAM | 🌍global | $0.44/GPU/hr | |||
RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 0 vCPU 0GB RAM | 🌍global | $0.57/GPU/hr |
RTX 5080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
RunPod | NVIDIA GeForce RTX 5080 16GB VRAM | 16GB | 0 vCPU 0GB RAM | 🌍global | $0.59/GPU/hr |
When to Choose the RTX 4000 Ada
The RTX 4000 Ada suits cost-sensitive deployments with rentals from $0.09 per hour and 130W TDP. Its 20 GB VRAM handles memory-bound tasks like loading extensive datasets or running multiple smaller models simultaneously. Low power enables dense cloud configurations without excessive energy costs.
When to Choose the RTX 5080
The RTX 5080 fits high-performance needs with 56.3 TFLOPS and 960 GB/s bandwidth. It excels in rapid training cycles or high-throughput inference, where speed justifies $0.25 per hour starting price. Bandwidth supports large-batch processing in generative AI workflows.
Use Cases
The RTX 5080's 56.3 TFLOPS in FP16 and FP32 doubles the RTX 4000 Ada's 26.7 TFLOPS, accelerating convergence on large models. Higher 960 GB/s bandwidth sustains large batches.
56.3 TFLOPS and 960 GB/s bandwidth enable higher request throughput than the RTX 4000 Ada's 26.7 TFLOPS and 360 GB/s. This reduces latency in production serving.
RTX 4000 Ada's 20 GB VRAM loads larger models without swapping, while RTX 5080's 56.3 TFLOPS speeds iterations. Choice depends on budget versus time.
960 GB/s bandwidth triples the RTX 4000 Ada's 360 GB/s, boosting image generation speed. 56.3 TFLOPS enhances diffusion model efficiency.
20 GB VRAM exceeds RTX 5080's 16 GB for complex simulations. Lower 130W TDP and $0.09 per hour pricing fit sustained, memory-heavy runs.
Frequently Asked Questions
Which GPU has more VRAM?▾
The RTX 4000 Ada provides 20 GB GDDR6 VRAM, surpassing the RTX 5080's 16 GB GDDR7. This benefits tasks requiring large in-memory datasets. Bandwidth compensates on the RTX 5080 at 960 GB/s versus 360 GB/s.
How do prices compare in the cloud?▾
RTX 4000 Ada rentals start at $0.09 per hour, averaging $0.21 per hour across 8 offers. RTX 5080 begins at $0.25 per hour, averaging $0.38 per hour across 4 offers. Cost reflects performance disparity.
What is the performance difference in TFLOPS?▾
RTX 5080 delivers 56.3 TFLOPS in FP16 and FP32, more than double the RTX 4000 Ada's 26.7 TFLOPS. This impacts training and inference speeds directly. Balanced FP16/FP32 suits mixed-precision workflows.
Which has higher memory bandwidth?▾
RTX 5080 achieves 960 GB/s with GDDR7, tripling RTX 4000 Ada's 360 GB/s GDDR6. Higher bandwidth supports larger batches in training. It mitigates the 16 GB VRAM limit.
What are the TDP values?▾
RTX 4000 Ada uses 130W TDP for efficiency, while RTX 5080 requires 360W. Lower TDP aids power-constrained environments. Higher TDP correlates with 56.3 TFLOPS output.
Which architecture is newer?▾
RTX 5080 uses Blackwell from 2025, succeeding RTX 4000 Ada's Ada Lovelace of 2023. Blackwell enables 56.3 TFLOPS gains. Both share PCIe form factors.
Which is cheaper to rent, the RTX 4000 Ada or the RTX 5080?▾
Cloud rental prices for both the RTX 4000 Ada and RTX 5080 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 4000 Ada have compared to the RTX 5080?▾
The RTX 4000 Ada has 20 GB of GDDR6 memory. The RTX 5080 has 16 GB of GDDR7 memory.
Can I find RTX 4000 Ada and RTX 5080 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 4000 Ada and the RTX 5080?▾
The RTX 4000 Ada uses the Ada Lovelace architecture (2023) while the RTX 5080 uses Blackwell (2025). The RTX 5080 delivers 2.1x the FP16 throughput and 2.7x the memory bandwidth of the RTX 4000 Ada.