Question 1

What AI models can run on A100 80GB PCIe?

Accepted Answer

The A100 80GB PCIe (80 GB VRAM) can run models including Llama-2-7b, Llama-2-7b-chat, NV-Llama2-13B-RLHF-RM, MediPhi-MedWiki, intent-aware-lfqa-qwen3-4b-baseline and more — 10 compatible models indexed so far. Compatible models are determined by whether the model's memory footprint fits within the GPU's 80 GB VRAM, potentially using quantization (Q8, Q6, or Q4) to reduce memory usage.

Question 2

What is the cheapest cloud option for A100 80GB PCIe?

Accepted Answer

The cheapest on-demand option for the A100 80GB PCIe is RunPod at $1.39/hr (1x_A100-80GB_SECURE). Spot/preemptible pricing is available at $1.39/hr. We track pricing across 26 providers to help you find the best deal.

Question 3

Is A100 80GB PCIe good for fine-tuning?

Accepted Answer

Yes, the A100 80GB PCIe is excellent for fine-tuning. With 80 GB of VRAM, it can handle full fine-tuning of models up to ~30B parameters and LoRA/QLoRA fine-tuning of much larger models. It's a top-tier choice for training workloads.

Question 4

How much VRAM does A100 80GB PCIe have?

Accepted Answer

The A100 80GB PCIe has 80 GB of VRAM (HBM2e). It also offers 1935 GB/s memory bandwidth, 312 TFLOPS of FP16 compute.

Question 5

What quantization formats work on A100 80GB PCIe?

Accepted Answer

The A100 80GB PCIe supports the following quantization formats: FP16 (full precision), Q8 (8-bit), Q6 (6-bit), Q4 (4-bit). FP16 works for models up to ~40B parameters. Q4 quantization lets models up to ~272B parameters (by VRAM estimate) fit on the A100 80GB PCIe.

Provider	On-demand	Spot	Actions
RunPod	$1.390/hr	$1.390/hr	Rent Get $5–$500 free
Microsoft Azure	$3.673/hr	$0.404/hr	—
Google Cloud	$3.928/hr	$1.309/hr	—

A100 80GB PCIe

Specifications

Cloud pricing

Compatible models

Compare this GPU

Frequently asked questions

VRAM	80 GB
Memory type	HBM2e
Bandwidth	1935 GB/s
FP16 TFLOPS	312
FP8 support	No