NVIDIA RTX 4000 Ada Generation VS NVIDIA RTX 4000 Ada Generation
Choosing between **RTX 4000 Ada** and **RTX 4000 Ada** depends on your specific AI workload requirements. Currently, you can rent these GPUs starting from **$0.00/h** and **$0.16/h** respectively across 7 providers.
RTX 4000 Ada
RTX 4000 Ada
📊 Detailed Specifications Comparison
| Specification | RTX 4000 Ada | RTX 4000 Ada | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Ada Lovelace | Ada Lovelace | - |
| Process Node | 4nm | 4nm | - |
| Target Market | professional | professional | - |
| Form Factor | Single-slot PCIe | Single-slot PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 20GB | 20GB | |
| Memory Type | GDDR6 | GDDR6 | - |
| Memory Bandwidth | 360 GB/s | 360 GB/s | |
| Memory Bus Width | 160-bit | 160-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 6,144 | 6,144 | |
| Tensor Cores (AI) | 192 | 192 | |
| RT Cores (Ray Tracing) | 48 | 48 | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 26.7 TFLOPS | 26.7 TFLOPS | |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 130W | 130W | |
| PCIe Interface | PCIe 4.0 x16 | PCIe 4.0 x16 | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA RTX 4000 Ada Generation
Higher VRAM capacity and memory bandwidth are critical for training large language models. The RTX 4000 Ada offers 20GB compared to 20GB.
AI Inference
NVIDIA RTX 4000 Ada Generation
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA RTX 4000 Ada Generation
Compare live pricing to find the best value for your specific workload.
Technical Deep Dive: RTX 4000 Ada vs RTX 4000 Ada
Both GPUs utilize the NVIDIA Ada Lovelace architecture. The primary difference lies in their compute core counts.
NVIDIA RTX 4000 Ada Generation is Best For:
- Compact workstations
- Professional graphics
- Deep learning training
NVIDIA RTX 4000 Ada Generation is Best For:
- Compact workstations
- Professional graphics
- Deep learning training
Frequently Asked Questions
Which GPU is better for AI training: RTX 4000 Ada or RTX 4000 Ada?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The RTX 4000 Ada offers 20GB of GDDR6 memory with 360 GB/s bandwidth, while the RTX 4000 Ada provides 20GB of GDDR6 with 360 GB/s bandwidth. Both GPUs have similar VRAM capacity, so performance characteristics become the deciding factor.
What is the price difference between RTX 4000 Ada and RTX 4000 Ada in the cloud?
Cloud GPU rental prices vary by provider and region. Check our price tracker for the latest rates from 50+ cloud providers.
Can I use RTX 4000 Ada instead of RTX 4000 Ada for my workload?
It depends on your specific requirements. If your model fits within 20GB of VRAM and you don't need the additional throughput of the RTX 4000 Ada, the RTX 4000 Ada can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the RTX 4000 Ada's architecture may be essential.
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