NVIDIA RTX A4000 VS NVIDIA RTX A2000
Choosing between **RTX A4000** and **RTX A2000** depends on your specific AI workload requirements. The **RTX A4000** 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 **$0.00/h** and **$0.05/h** respectively across 2 providers.
RTX A4000
📊 Detailed Specifications Comparison
| Specification | RTX A4000 | RTX A2000 | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Ampere | Ampere | - |
| Process Node | 8nm | 8nm | - |
| Target Market | professional | professional | - |
| Form Factor | Single-slot PCIe | Low-profile PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 16GB | 12GB | +33% |
| Memory Type | GDDR6 | GDDR6 | - |
| Memory Bandwidth | 448 GB/s | 288 GB/s | +56% |
| Memory Bus Width | 256-bit | 192-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 6,144 | 3,328 | +85% |
| Tensor Cores (AI) | 192 | 104 | +85% |
| RT Cores (Ray Tracing) | 48 | 26 | +85% |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 19.2 TFLOPS | 8 TFLOPS | +140% |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 140W | 70W | +100% |
| PCIe Interface | PCIe 4.0 x16 | PCIe 4.0 x16 | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA RTX A4000
Higher VRAM capacity and memory bandwidth are critical for training large language models. The RTX A4000 offers 16GB compared to 12GB.
AI Inference
NVIDIA RTX A4000
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA RTX A2000
Compare live pricing to find the best value for your specific workload.
Technical Deep Dive: RTX A4000 vs RTX A2000
Both GPUs utilize the NVIDIA Ampere architecture. The primary difference lies in their memory capacity and compute core counts.
NVIDIA RTX A4000 is Best For:
- Professional graphics
- Workstation AI
- High-end training
NVIDIA RTX A2000 is Best For:
- Compact workstations
- Professional graphics
- AI workloads
Frequently Asked Questions
Which GPU is better for AI training: RTX A4000 or RTX A2000?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The RTX A4000 offers 16GB of GDDR6 memory with 448 GB/s bandwidth, while the RTX A2000 provides 12GB of GDDR6 with 288 GB/s bandwidth. For larger models, the RTX A4000's higher VRAM capacity gives it an advantage.
What is the price difference between RTX A4000 and RTX A2000 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 A2000 instead of RTX A4000 for my workload?
It depends on your specific requirements. If your model fits within 12GB of VRAM and you don't need the additional throughput of the RTX A4000, the RTX A2000 can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the RTX A4000's architecture may be essential.
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