Specifications Compared
| Spec | RTX-5080 | T4 |
|---|---|---|
| TDP | 360W | 70W |
| VRAM | 16 GB | 16 GB |
| CUDA Cores | 10,752 | 2,560 |
| Memory Type | GDDR7 | GDDR6 |
| Architecture | Blackwell | Turing |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 336 | 320 |
| FP16 Performance | 56.3 TFLOPS | 8.1 TFLOPS |
| FP32 Performance | 56.3 TFLOPS | 8.1 TFLOPS |
| INT8 Performance | 900 TOPS | 130 TOPS |
| Memory Bandwidth | 960 GB/s | 320 GB/s |
Performance Analysis
The RTX 5080's 56.3 TFLOPS FP16 performance accelerates deep learning training by approximately 7x over the T4's 8.1 TFLOPS, enabling faster iterations on large models. FP32 parity at these rates supports general compute tasks similarly, but the RTX 5080 handles mixed-precision workflows with superior throughput. In inference scenarios, this translates to higher queries per second for real-time applications.
Memory bandwidth disparities prove critical: the RTX 5080's 960 GB/s allows larger batch sizes without bottlenecks, ideal for training datasets exceeding 320 GB/s limits on the T4. This reduces latency in data-intensive operations like image generation or simulations.
Power consumption differs markedly at 360 W TDP for the RTX 5080 versus 70 W for the T4, suiting high-performance clusters over power-sensitive deployments. Overall, these specs position the RTX 5080 for demanding AI pipelines, while the T4 fits lightweight, efficient inference.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
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 |
T4
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 AWS | NVIDIA Tesla T4 16GB VRAM | 16GB | 4 vCPU 16GB RAM | Virginia | $0.53/GPU/hr | |||
AWS | NVIDIA Tesla T4 16GB VRAM | 16GB | 8 vCPU 32GB RAM | Virginia | $0.75/GPU/hr | |||
AWS | 4×NVIDIA Tesla T4 16GB VRAM | 16GB | 48 vCPU 192GB RAM | Virginia | $0.98/GPU/hr $3.91/hr total (4×) | |||
AWS | NVIDIA Tesla T4 16GB VRAM | 16GB | 16 vCPU 64GB RAM | Virginia | $1.20/GPU/hr | |||
AWS | NVIDIA Tesla T4 16GB VRAM | 16GB | 32 vCPU 128GB RAM | Virginia | $2.18/GPU/hr |
When to Choose the RTX 5080
Select the RTX 5080 for compute-intensive tasks such as large-scale model training or high-resolution generative AI, where 56.3 TFLOPS FP16 outperforms the T4's 8.1 TFLOPS. Its 960 GB/s bandwidth supports expansive batch sizes, crucial for modern workflows. At an average cloud price of $0.38 per hour, it delivers superior value for performance-driven users.
The Blackwell architecture excels in cutting-edge applications requiring post-2018 optimizations unavailable on Turing.
When to Choose the T4
Choose the T4 for low-power inference deployments, such as edge computing or always-on services, where its 70 W TDP minimizes energy costs compared to the RTX 5080's 360 W. Legacy software stacks optimized for Turing benefit from its proven stability in lightweight tasks.
Despite higher average pricing at $1.66 per hour, the T4 suits scenarios prioritizing minimal thermal overhead over peak throughput.
Use Cases
The RTX 5080's 56.3 TFLOPS FP16 vastly outperforms the T4's 8.1 TFLOPS, enabling faster training of large language models.
Higher 960 GB/s bandwidth on the RTX 5080 supports larger batches for efficient inference, reducing latency over the T4's 320 GB/s.
RTX 5080's superior FP32 at 56.3 TFLOPS accelerates fine-tuning iterations compared to T4's 8.1 TFLOPS.
The RTX 5080 handles high-resolution image generation swiftly with 56.3 TFLOPS and 16 GB GDDR7, outperforming T4 capabilities.
RTX 5080's 960 GB/s bandwidth and 56.3 TFLOPS FP32 excel in simulations, surpassing T4's metrics for complex datasets.
Frequently Asked Questions
What is the performance difference between RTX 5080 and T4?▾
The RTX 5080 delivers 56.3 TFLOPS in FP16 and FP32, compared to the T4's 8.1 TFLOPS, a nearly 7x advantage. This impacts training and inference speeds significantly.
Do RTX 5080 and T4 have the same VRAM?▾
Both provide 16 GB of VRAM, RTX 5080 with GDDR7 and T4 with GDDR6. Bandwidth differs at 960 GB/s versus 320 GB/s.
Which GPU is cheaper in the cloud?▾
RTX 5080 starts at $0.25 per hour with an average of $0.38 per hour across four offers. T4 averages $1.66 per hour across six offers.
What are the TDP ratings?▾
RTX 5080 has a 360 W TDP, suitable for high-performance setups. T4 operates at 70 W for power-efficient environments.
Which architecture is newer?▾
RTX 5080 uses Blackwell from 2025, while T4 relies on Turing from 2018. This generational gap affects modern AI optimizations.
Are both GPUs available in PCIe form factor?▾
Yes, both RTX 5080 and T4 support PCIe, facilitating easy integration in cloud instances.
Which is cheaper to rent, the RTX 5080 or the T4?▾
Cloud rental prices for both the RTX 5080 and T4 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 5080 have compared to the T4?▾
The RTX 5080 has 16 GB of GDDR7 memory. The T4 has 16 GB of GDDR6 memory.
Can I find RTX 5080 and T4 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 5080 and the T4?▾
The RTX 5080 uses the Blackwell architecture (2025) while the T4 uses Turing (2018). The RTX 5080 delivers 7.0x the FP16 throughput and 3.0x the memory bandwidth of the T4.