About the NVIDIA A100 80GB
The NVIDIA A100 80GB is the workhorse of cloud ML in 2026. Released in 2020 on the Ampere architecture, it remains widely deployed, broadly available across all major clouds, and significantly cheaper than the H100 while still capable of training 70B-parameter models. The 80GB variant is particularly valuable for large model fine-tuning where memory matters more than peak throughput.
Specs
Memory
80 GB HBM2e
Bandwidth
2.0 TB/s
Tensor cores
432 (3rd gen)
FP16 (peak)
624 TFLOPS
Architecture
Ampere
Released
Q2 2020
What's it good for?
- Fine-tuning 7B–70B models — most fine-tuning workloads run perfectly on A100 80GB without needing H100 prices.
- Mid-scale inference — Llama 3 8B, 13B served at production volumes.
- Computer vision training — ResNet, YOLO, Vision Transformers.
- Academic research — broad availability and lower cost make A100 the go-to for grad student / lab work.
When to use A100 80GB vs alternatives
- A100 80GB vs A100 40GB: the 80GB variant fits larger models (Llama 13B+ in BF16) without offloading. Worth the ~30% premium for training, less critical for inference.
- A100 vs H100: H100 is 2-3× faster but typically 2× the price. A100 is better cost/performance for jobs under 6 hours; H100 wins beyond that.
- A100 vs RTX 4090: 4090 has more raw FP16 throughput at a fraction of the cost, but only 24GB. Use 4090 for models that fit; A100 80GB for those that don't.