Table of Contents
The A100 40 GB is older but datacenter-class — ECC, NVLink, certified drivers. The 5060 Ti is consumer Blackwell. Both fit 7B FP8 comfortably.
TL;DR
For pure 7B-8B inference: 5060 Ti FP8 is faster per pound. A100 40 GB wins on HBM bandwidth (1.55 TB/s vs 448 GB/s) and NVLink for multi-GPU. For training, A100 wins decisively.
Specs
| Spec | 5060 Ti 16 GB | A100 40 GB |
|---|---|---|
| Architecture | Blackwell (2025) | Ampere (2020) |
| VRAM | 16 GB GDDR7 | 40 GB HBM2 |
| Memory bandwidth | 448 GB/s | 1,555 GB/s |
| FP16 TFLOPS | ~24 | ~312 |
| FP8 hardware | Yes | No |
| NVLink | No | Yes |
| ECC | No | Yes |
Benchmarks
- Mistral 7B FP8: 5060 Ti 880 tok/s, A100 40 GB ~1,150 tok/s (FP16, no FP8 hw)
- FP16 only A100 has higher absolute throughput but no FP8 path
Verdict
For new 7B-8B inference deployments, the 5060 Ti is the right pick (cheaper, FP8). A100 40 GB shines on training, multi-GPU NVLink builds, and 13B+ FP16 (40 GB headroom).
Bottom line
5060 Ti for inference, A100 for training and multi-GPU. See A100 hosting.
