NVIDIA A100 80GB VS NVIDIA Tesla V100S
Choosing between **A100 80GB** and **V100S** depends on your specific AI workload requirements. The **A100 80GB** 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 **$0.40/h** and **$0.88/h** respectively across 42 providers.
A100 80GB
📊 Detailed Specifications Comparison
| Specification | A100 80GB | V100S | Difference |
|---|---|---|---|
| Architecture & Design | |||
| Architecture | Ampere | Volta | - |
| Process Node | 7nm | 12nm | - |
| Target Market | datacenter | datacenter | - |
| Form Factor | SXM4 / PCIe | Dual-slot PCIe | - |
| Memory & Bandwidth | |||
| VRAM Capacity | 80GB | 32GB | +150% |
| Memory Type | HBM2e | HBM2 | - |
| Memory Bandwidth | 2.0 TB/s | 1.1 TB/s | +80% |
| Memory Bus Width | 5120-bit | 4096-bit | - |
| Compute Infrastructure | |||
| CUDA Cores | 6,912 | 5,120 | +35% |
| Tensor Cores (AI) | 432 | N/A | |
| AI & Compute Performance (TFLOPS) | |||
| FP32 (Single Precision) | 19.5 TFLOPS | 16.4 TFLOPS | +19% |
| FP16 (Half Precision) | 312 TFLOPS | N/A | |
| 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 3.0 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 32GB.
AI Inference
NVIDIA A100 80GB
For inference workloads, performance per watt matters most. Consider the balance between FP16/INT8 throughput and power consumption.
Budget-Conscious Choice
NVIDIA A100 80GB
Based on current cloud pricing, the A100 80GB starts at a lower hourly rate.
Technical Deep Dive: A100 80GB vs V100S
This is a generational comparison within the NVIDIA ecosystem, pitting Ampere against Volta. The A100 80GB has a significant **48GB VRAM advantage**, which is crucial for training massive datasets or large language models. From a cost perspective, the **A100 80GB** is currently about **55% cheaper** per hour, offering better value for budget-conscious projects.
NVIDIA A100 80GB is Best For:
- AI model training
- Scientific computing
- Newest FP8 precision workloads
NVIDIA Tesla V100S is Best For:
- HPC
- Scientific computing
- Legacy architectures
Frequently Asked Questions
Which GPU is better for AI training: A100 80GB or V100S?
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 V100S provides 32GB of HBM2 with 1.1 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 V100S in the cloud?
Cloud GPU rental prices vary by provider and region. Based on our data, A100 80GB starts at $0.40/hour while V100S starts at $0.88/hour. This represents a 55% price difference.
Can I use V100S instead of A100 80GB for my workload?
It depends on your specific requirements. If your model fits within 32GB of VRAM and you don't need the additional throughput of the A100 80GB, the V100S 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.