Specifications Compared
| Spec | RTX-2070 | T4 |
|---|---|---|
| TDP | 175W | 70W |
| VRAM | 8 GB | 16 GB |
| CUDA Cores | 2,304 | 2,560 |
| Memory Type | GDDR6 | GDDR6 |
| Architecture | Turing | Turing |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 288 | 320 |
| FP16 Performance | 7.5 TFLOPS | 8.1 TFLOPS |
| FP32 Performance | 7.5 TFLOPS | 8.1 TFLOPS |
| Memory Bandwidth | 448 GB/s | 320 GB/s |
Performance Analysis
The RTX 2070 SUPER's higher 9.1 TFLOPS FP32 performance exceeds the T4's 8.1 TFLOPS, enabling faster model training and inference for workloads fitting within 8 GB VRAM. FP16 performance follows suit at 9.1 TFLOPS versus 8.1 TFLOPS, benefiting half-precision tasks common in deep learning. This compute edge suits single-GPU training runs or gaming-adjacent simulations.
Memory bandwidth of 448 GB/s on the RTX 2070 SUPER supports larger batch sizes than the T4's 320 GB/s, reducing data loading bottlenecks in training loops. However, the T4's 16 GB VRAM accommodates larger models or bigger batches without swapping, crucial for inference on extensive language models. The T4's 70 W TDP allows dense server deployments, contrasting the RTX 2070 SUPER's 215 W draw which limits scalability in power-constrained environments.
These differences mean the RTX 2070 SUPER excels in bandwidth-intensive tasks, while the T4 prioritizes VRAM capacity and efficiency for production inference.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
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 2070 SUPER
Select the RTX 2070 SUPER for local workstations handling gaming, content creation, or machine learning with moderate VRAM needs. Its 448 GB/s bandwidth and 9.1 TFLOPS FP32 performance accelerate Stable Diffusion generation or fine-tuning models under 8 GB. The 215 W TDP fits desktop builds where cloud access is unavailable.
This GPU suits hobbyists or developers prioritizing raw speed over capacity, especially without live cloud offers.
When to Choose the Tesla T4
Choose the Tesla T4 for cloud-based inference or multi-GPU clusters requiring low power and high VRAM. Its 16 GB GDDR6 handles larger batch sizes in LLM serving, with 70 W TDP enabling cost-effective scaling. Current pricing from $0.53 per hour makes it ideal for production deployments.
The T4 outperforms in VRAM-bound tasks despite lower 320 GB/s bandwidth, suiting enterprise inference at average $1.66 per hour.
Use Cases
The T4's 16 GB VRAM fits larger models essential for LLM training, avoiding out-of-memory errors common with the RTX 2070 SUPER's 8 GB. Cloud pricing from $0.53 per hour supports extended runs.
T4 excels with 16 GB VRAM for batch inference on LLMs, and 70 W TDP enables dense serving. Pricing averages $1.66 per hour across 6 offers.
RTX 2070 SUPER's 9.1 TFLOPS and 448 GB/s bandwidth speed smaller fine-tunes, while T4's 16 GB VRAM handles bigger datasets. Choice depends on model size.
RTX 2070 SUPER's higher 9.1 TFLOPS FP16 and 448 GB/s bandwidth generate images faster within 8 GB VRAM limits for standard resolutions.
RTX 2070 SUPER's 9.1 TFLOPS FP32 outperforms T4's 8.1 TFLOPS for simulations, with bandwidth aiding data-heavy computations.
Frequently Asked Questions
Which GPU has more VRAM?▾
The Tesla T4 provides 16 GB GDDR6 VRAM, doubling the RTX 2070 SUPER's 8 GB. This makes the T4 better for large models. Bandwidth favors the SUPER at 448 GB/s over 320 GB/s.
What is the performance difference?▾
RTX 2070 SUPER offers 9.1 TFLOPS in FP16 and FP32, surpassing T4's 8.1 TFLOPS. This translates to faster training on smaller datasets. T4 compensates with more VRAM.
Which has lower power consumption?▾
The T4 uses 70 W TDP, far below the RTX 2070 SUPER's 215 W. This enables more efficient cloud deployments. Both use PCIe form factor.
Is the T4 available in the cloud?▾
Yes, T4 cloud pricing starts at $0.53 per hour, averaging $1.66 per hour across 6 offers. RTX 2070 SUPER has no live cloud offers.
Can these GPUs connect via NVLink?▾
Neither supports NVLink interconnect. Both rely on PCIe for multi-GPU setups. T4 suits datacenter scaling differently.
Which is better for inference?▾
T4 is preferable for inference due to 16 GB VRAM and low 70 W TDP. It handles larger batches efficiently at $0.53 per hour minimum.
Which is cheaper to rent, the RTX 2070 or the T4?▾
Cloud rental prices for both the RTX 2070 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 2070 have compared to the T4?▾
The RTX 2070 has 8 GB of GDDR6 memory. The T4 has 16 GB of GDDR6 memory.
Can I find RTX 2070 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 2070 and the T4?▾
The RTX 2070 uses the Turing architecture (2018) while the T4 uses Turing (2018). The T4 delivers 1.1x the FP16 throughput and 1.4x the memory bandwidth of the RTX 2070.