NVIDIA GeForce RTX 4070 Ti SUPER VS NVIDIA GeForce RTX 4090
Choosing between **RTX 4070 Ti Super** and **RTX 4090** depends on your specific AI workload requirements. The **RTX 4090** leads in both memory capacity and raw compute power, making it a stronger choice for high-end LLM training. Currently, you can rent these GPUs starting from **$0.11/h** and **$0.18/h** respectively across 12 providers.
RTX 4070 Ti Super
RTX 4090
📊 Detailed Specifications Comparison
| Specification | RTX 4070 Ti Super | RTX 4090 | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Ada Lovelace | Ada Lovelace | - |
| Process Node | 4nm | 4nm | - |
| Target Market | consumer | consumer | - |
| Form Factor | Dual-slot PCIe | 3-slot PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 16GB | 24GB | -33% |
| Memory Type | GDDR6X | GDDR6X | - |
| Memory Bandwidth | 672 GB/s | 1.01 TB/s | -33% |
| Memory Bus Width | 256-bit | 384-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 8,448 | 16,384 | -48% |
| Tensor Cores (AI) | 264 | 512 | -48% |
| RT Cores (Ray Tracing) | 66 | 128 | -48% |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 44.1 TFLOPS | 82.58 TFLOPS | -47% |
| FP16 (Half Precision) | N/A | 165.15 TFLOPS | |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 285W | 450W | -37% |
| PCIe Interface | PCIe 4.0 x16 | PCIe 4.0 x16 | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA GeForce RTX 4090
Higher VRAM capacity and memory bandwidth are critical for training large language models. The RTX 4090 offers 24GB compared to 16GB.
AI Inference
NVIDIA GeForce RTX 4090
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA GeForce RTX 4070 Ti SUPER
Based on current cloud pricing, the RTX 4070 Ti Super starts at a lower hourly rate.
Technical Deep Dive: RTX 4070 Ti Super vs RTX 4090
Both GPUs utilize the NVIDIA Ada Lovelace architecture. The primary difference lies in their memory capacity and compute core counts. The RTX 4090 has a significant **8GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **RTX 4070 Ti Super** is currently about **39% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA GeForce RTX 4070 Ti SUPER is Best For:
- AI development
- Gaming
- Enterprise training
NVIDIA GeForce RTX 4090 is Best For:
- Image generation
- AI development
- Enterprise production
Frequently Asked Questions
Which GPU is better for AI training: RTX 4070 Ti Super or RTX 4090?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The RTX 4070 Ti Super offers 16GB of GDDR6X memory with 672 GB/s bandwidth, while the RTX 4090 provides 24GB of GDDR6X with 1.01 TB/s bandwidth. For larger models, the RTX 4090's higher VRAM capacity gives it an advantage.
What is the price difference between RTX 4070 Ti Super and RTX 4090 in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, RTX 4070 Ti Super starts at $0.11/hour while RTX 4090 starts at $0.18/hour. This represents a 39% price difference.
Can I use RTX 4090 instead of RTX 4070 Ti Super for my workload?
It depends on your specific requirements. If your model fits within 24GB of VRAM and you don't need the additional throughput of the RTX 4070 Ti Super, the RTX 4090 can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the RTX 4070 Ti Super's architecture may be essential.
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