NVIDIA A100 80GB VS NVIDIA A100 40GB
Choosing between **A100 80GB** and **A100 40GB** depends on your specific AI workload requirements. While the **A100 80GB** offers more VRAM for larger models, the **A100 40GB** remains competitive in other areas. Currently, you can rent these GPUs starting from **$0.40/h** and **$0.00/h** respectively across 41 providers.
A100 80GB
A100 40GB
📊 Detailed Specifications Comparison
| Specification | A100 80GB | A100 40GB | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Ampere | Ampere | - |
| Process Node | 7nm | 7nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | SXM4 / PCIe | SXM4 / PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 80GB | 40GB | +100% |
| Memory Type | HBM2e | HBM2 | - |
| Memory Bandwidth | 2.0 TB/s | 1.5 TB/s | +31% |
| Memory Bus Width | 5120-bit | 5120-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 6,912 | 6,912 | |
| Tensor Cores (AI) | 432 | 432 | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 19.5 TFLOPS | 19.5 TFLOPS | |
| FP16 (Half Precision) | 312 TFLOPS | 312 TFLOPS | |
| TF32 (Tensor Float) | 156 TFLOPS | N/A | |
| FP64 (Double Precision) | 9.7 TFLOPS | N/A | |
| INT8 (Integer Precision) | 624 TOPS | N/A | |
| Power & Efficiency | |||
| TDP (Thermal Design Power) | 400W | 250W | +60% |
| PCIe Interface | PCIe 4.0 x16 | PCIe 4.0 x16 | - |
| Multi-GPU Interconnect | NVLink 3.0 (600 GB/s) | None | - |
🎯 Use Case Recommendations
LLM & Large Model Training
NVIDIA A100 80GB
Higher VRAM capacity and memory bandwidth are critical for training large language models. The A100 80GB offers 80GB compared to 40GB.
AI Inference
NVIDIA A100 40GB
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA A100 80GB
Compare live pricing to find the best value for your specific workload.
Technical Deep Dive: A100 80GB vs A100 40GB
Both GPUs utilize the NVIDIA Ampere architecture. The primary difference lies in their memory capacity and compute core counts. The A100 80GB has a significant **40GB VRAM advantage**, which is crucial for training massive datasets or large language models.
NVIDIA A100 80GB is Best For:
- AI model training
- Scientific computing
- Newest FP8 precision workloads
NVIDIA A100 40GB is Best For:
- Mainstream AI training
- Scientific computing
- Memory-intensive LLM training
Frequently Asked Questions
Which GPU is better for AI training: A100 80GB or A100 40GB?
For AI training, the key factors are VRAM size, memory bandwidth, and tensor core performance. The A100 80GB offers 80GB of HBM2e memory with 2.0 TB/s bandwidth, while the A100 40GB provides 40GB of HBM2 with 1.5 TB/s bandwidth. For larger models, the A100 80GB's higher VRAM capacity gives it an advantage.
What is the price difference between A100 80GB and A100 40GB 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 A100 40GB instead of A100 80GB for my workload?
It depends on your specific requirements. If your model fits within 40GB of VRAM and you don't need the additional throughput of the A100 80GB, the A100 40GB can be a cost-effective alternative. However, for workloads requiring maximum memory capacity or multi-GPU scaling, the A100 80GB's NVLink support (NVLink 3.0 (600 GB/s)) may be essential.
Ready to rent a GPU?
Compare live pricing across 50+ cloud providers and find the best deal.