Specifications Compared
| Spec | RTX-A4000 | T4 |
|---|---|---|
| TDP | 140W | 70W |
| VRAM | 16 GB | 16 GB |
| CUDA Cores | 6,144 | 2,560 |
| Memory Type | GDDR6 | GDDR6 |
| Architecture | Ampere | Turing |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 192 | 320 |
| FP16 Performance | 19.2 TFLOPS | 8.1 TFLOPS |
| FP32 Performance | 19.2 TFLOPS | 8.1 TFLOPS |
| Memory Bandwidth | 448 GB/s | 320 GB/s |
Performance Analysis
Compute differences dominate real-world implications: the RTX A4500's 23.7 TFLOPS FP16 and FP32 rates deliver nearly three times the T4's 8.1 TFLOPS, accelerating deep learning training and inference by enabling quicker iterations on large datasets. FP16 performance directly benefits mixed-precision training, where the A4500 processes operations 2.9 times faster.
Memory bandwidth of 640 GB/s on the A4500 supports larger batch sizes during training, minimizing data loading bottlenecks unlike the T4's 320 GB/s limit. The A4500's 20 GB VRAM capacity handles bigger models without swapping, while the T4's 16 GB suits smaller workloads. Higher TDP at 200 W on the A4500 sustains peak performance under load, contrasting the T4's 70 W for low-power scenarios.
Overall, these specs make the A4500 superior for throughput-intensive tasks, though the T4 conserves energy in scale-out inference.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX A4500
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA RTX A4000 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Tallinn, Harjumaa | $0.08/GPU/hr | Available | ||
 Vast.ai | 8×NVIDIA RTX A4000 16GB VRAM | 16GB | 80 vCPU 201GB RAM 1698GB Storage | United Kingdom | $0.15/GPU/hr $1.17/hr total (8×) | Available | ||
 Hyperstack | 4×NVIDIA RTX A4000 16GB VRAM | 16GB | 16 vCPU 86GB RAM 500GB Storage | Norway | $0.15/GPU/hr $0.60/hr total (4×) | Available | ||
Hyperstack | 2×NVIDIA RTX A4000 16GB VRAM | 16GB | 8 vCPU 43GB RAM 200GB Storage | Norway | $0.15/GPU/hr $0.30/hr total (2×) | Available | ||
Hyperstack | NVIDIA RTX A4000 16GB VRAM | 16GB | 4 vCPU 21GB RAM 100GB Storage | Norway | $0.15/GPU/hr | Available |
Tesla 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 A4500
Select the RTX A4500 for compute-heavy workloads like model training and fine-tuning. Its 23.7 TFLOPS FP16/FP32 outperforms the T4's 8.1 TFLOPS, reducing training times significantly. The 640 GB/s bandwidth and 20 GB VRAM enable larger batches and models at a low $0.10 per hour starting price.
When to Choose the Tesla T4
Opt for the Tesla T4 in power-limited environments such as dense cloud instances. Its 70 W TDP consumes half the energy of the A4500's 200 W, fitting multi-GPU setups. The T4's 8.1 TFLOPS suffices for basic inference where cost scales with low utilization.
Use Cases
The A4500's 23.7 TFLOPS FP16/FP32 enables 2.9 times faster training than the T4's 8.1 TFLOPS. Higher 640 GB/s bandwidth supports large batches.
20 GB VRAM on the A4500 accommodates bigger models than T4's 16 GB. 23.7 TFLOPS delivers higher throughput for real-time serving.
Ampere architecture and 640 GB/s bandwidth accelerate fine-tuning iterations over T4's 320 GB/s. Lower $0.10/hr pricing adds value.
A4500's higher FP16 performance at 23.7 TFLOPS speeds image generation. 20 GB VRAM handles high-resolution tasks efficiently.
T4's 70 W TDP suits power-sensitive simulations at 8.1 TFLOPS. A4500's 23.7 TFLOPS excels if speed is prioritized.
Frequently Asked Questions
Which GPU has higher performance, RTX A4500 or T4?▾
The RTX A4500 achieves 23.7 TFLOPS in FP16 and FP32. The T4 reaches 8.1 TFLOPS. This gives the A4500 a 2.9 times advantage in compute tasks.
What are the VRAM differences between RTX A4500 and T4?▾
RTX A4500 provides 20 GB GDDR6 VRAM. T4 offers 16 GB GDDR6. The extra capacity on A4500 supports larger AI models.
How do memory bandwidths compare?▾
RTX A4500 delivers 640 GB/s bandwidth. T4 provides 320 GB/s. Higher bandwidth on A4500 enables larger batch sizes in training.
What are the current cloud prices for these GPUs?▾
RTX A4500 starts from $0.10 per hour, averaging $0.19 per hour across 4 offers. T4 starts from $0.53 per hour, averaging $1.66 per hour across 6 offers.
Which GPU uses less power?▾
The T4 has a 70 W TDP. RTX A4500 requires 200 W. T4 suits energy-constrained deployments.
Is RTX A4500 newer than T4?▾
RTX A4500 uses Ampere architecture from 2021. T4 employs Turing from 2018. The generational gap provides A4500 with architectural improvements.
Which is cheaper to rent, the RTX A4000 or the T4?▾
Cloud rental prices for both the RTX A4000 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 A4000 have compared to the T4?▾
The RTX A4000 has 16 GB of GDDR6 memory. The T4 has 16 GB of GDDR6 memory.
Can I find RTX A4000 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 A4000 and the T4?▾
The RTX A4000 uses the Ampere architecture (2021) while the T4 uses Turing (2018). The RTX A4000 delivers 2.4x the FP16 throughput and 1.4x the memory bandwidth of the T4.