Specifications Compared
| Spec | RTX-4070 | T4 |
|---|---|---|
| TDP | 200W | 70W |
| VRAM | 12 GB | 16 GB |
| CUDA Cores | 5,888 | 2,560 |
| Memory Type | GDDR6X | GDDR6 |
| Architecture | Ada Lovelace | Turing |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 184 | 320 |
| FP16 Performance | 29.1 TFLOPS | 8.1 TFLOPS |
| FP32 Performance | 29.1 TFLOPS | 8.1 TFLOPS |
| INT8 Performance | 466 TOPS | 130 TOPS |
| Memory Bandwidth | 504 GB/s | 320 GB/s |
Performance Analysis
Compute throughput defines the core difference: the RTX 4070 Ti SUPER's 44.1 TFLOPS in FP16 and FP32 provides over 5 times the capability of the T4's 8.1 TFLOPS, yielding faster model training epochs and higher inference throughput for deep learning pipelines. This delta suits training where FP16 mixed precision accelerates convergence without accuracy loss. Higher memory bandwidth on the RTX 4070 Ti SUPER at 672 GB/s versus 320 GB/s enables larger batch sizes in memory-bound tasks like transformer models, minimizing data transfer bottlenecks during inference or fine-tuning. The T4's narrower bandwidth limits scalability for large datasets. Power efficiency varies: the T4's 70 W TDP supports dense server racks, but the RTX 4070 Ti SUPER's 285 W unlocks peak performance for demanding workloads despite increased cooling needs.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 4070 Ti SUPER
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4070 Ti 12GB VRAM | 12GB | 6 vCPU 30GB RAM | 🌍global | $0.50/GPU/hr |
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 4070 Ti SUPER
The RTX 4070 Ti SUPER excels in high-throughput scenarios such as LLM fine-tuning or Stable Diffusion generation, where 44.1 TFLOPS FP32 and 672 GB/s bandwidth process complex models rapidly. Its cloud pricing from $0.09 per hour delivers superior performance per dollar compared to the T4. Modern Ada Lovelace features enhance tensor operations for contemporary AI frameworks.
When to Choose the Tesla T4
The T4 suits low-power inference deployments, leveraging its 70 W TDP for high-density servers running lightweight models. Legacy Turing-optimized software benefits from its 16 GB VRAM and 8.1 TFLOPS at lower latency for edge cases. It fits budgets prioritizing power efficiency over raw speed despite higher $1.66 per hour average.
Use Cases
The RTX 4070 Ti SUPER's 44.1 TFLOPS FP16 enables 5 times faster training than the T4's 8.1 TFLOPS. Higher 672 GB/s bandwidth supports larger models.
44.1 TFLOPS FP32 on the RTX 4070 Ti SUPER delivers superior throughput for batched requests versus the T4's 8.1 TFLOPS. Lower $0.17 per hour cost improves scalability.
Ada Lovelace architecture with 672 GB/s bandwidth handles parameter-efficient tuning efficiently, outpacing the T4's 320 GB/s.
RTX 4070 Ti SUPER's 16 GB GDDR6X and 44.1 TFLOPS accelerate image generation far beyond the T4's capabilities.
T4's 70 W TDP suits power-constrained HPC nodes; RTX 4070 Ti SUPER's 44.1 TFLOPS fits compute-intensive simulations.
Frequently Asked Questions
Which GPU has higher compute performance?▾
The RTX 4070 Ti SUPER offers 44.1 TFLOPS in FP16 and FP32, exceeding the T4's 8.1 TFLOPS by more than 5 times. This impacts training and inference speeds directly. Bandwidth at 672 GB/s further amplifies its advantage.
How do VRAM and bandwidth compare?▾
Both have 16 GB VRAM, but the RTX 4070 Ti SUPER uses GDDR6X with 672 GB/s bandwidth versus the T4's GDDR6 at 320 GB/s. Larger batches are feasible on the RTX 4070 Ti SUPER. This aids memory-intensive AI tasks.
What are the power and pricing differences?▾
RTX 4070 Ti SUPER TDP is 285 W with cloud pricing from $0.09 per hour averaging $0.17; T4 is 70 W from $0.53 averaging $1.66. Lower power favors T4 in dense setups. Cost per hour strongly prefers RTX 4070 Ti SUPER.
Is RTX 4070 Ti SUPER better for inference?▾
Yes, its 44.1 TFLOPS and 672 GB/s bandwidth enable higher throughput than T4's 8.1 TFLOPS and 320 GB/s. Pricing at $0.17 average enhances value. T4 suits low-latency niche inference.
Which architecture is newer?▾
RTX 4070 Ti SUPER uses Ada Lovelace from 2024; T4 uses Turing from 2018. Ada supports advanced tensor cores for modern ML. This generational leap boosts efficiency.
Best for Stable Diffusion?▾
RTX 4070 Ti SUPER dominates with 44.1 TFLOPS and 16 GB GDDR6X at 672 GB/s, generating images faster than T4. Cloud cost at $0.09 minimum accelerates workflows. T4 lags in diffusion model performance.
Which is cheaper to rent, the RTX 4070 or the T4?▾
Cloud rental prices for both the RTX 4070 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 4070 have compared to the T4?▾
The RTX 4070 has 12 GB of GDDR6X memory. The T4 has 16 GB of GDDR6 memory.
Can I find RTX 4070 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 4070 and the T4?▾
The RTX 4070 uses the Ada Lovelace architecture (2023) while the T4 uses Turing (2018). The RTX 4070 delivers 3.6x the FP16 throughput and 1.6x the memory bandwidth of the T4.