Comparison

NVIDIA A100 40GB vs NVIDIA A100 80GB

Same compute, double the memory

Both A100 variants deliver identical 312 FP16 TFLOPS. The 80GB version has double the HBM2e memory, enabling larger model training at approximately 30% higher cost per hour.

Pricing Comparison

Specifications

Specification	NVIDIA A100 40GB	NVIDIA A100 80GB
Manufacturer	NVIDIA	NVIDIA
Architecture	Ampere	Ampere
Accelerator Type	GPU	GPU
Primary Use	training	training
Memory (VRAM)	40 GB	80 GB
FP16 Performance	312 TFLOPS	312 TFLOPS
TDP	400W	400W
Perf per Watt	0.78 TFLOPS/W	0.78 TFLOPS/W

Detailed Analysis

The A100 40GB and 80GB are identical in compute architecture — same Ampere GPU, same 312 FP16 TFLOPS, same Tensor Core configuration. The only difference is memory capacity: 40GB vs 80GB of HBM2e.

This memory difference determines which models you can train or serve. The 40GB variant can handle models up to approximately 15 billion parameters (depending on batch size and optimiser), while the 80GB variant extends this to roughly 30 billion parameters on a single GPU.

For inference, the 40GB is often sufficient for models up to 13B parameters with quantisation. The 80GB is necessary for serving larger models or running multiple models simultaneously using MIG.

The price difference is typically 25-35%, making the 80GB variant a straightforward choice when your workload needs the extra memory. If your models fit comfortably in 40GB, the 40GB variant saves meaningful cost per hour.

Verdict

Best for Training

80GB for models >15B parameters or large batch sizes. 40GB for smaller models where it saves 25-35% per hour.

Best for Inference

40GB is sufficient for most inference. 80GB when serving 13B+ parameter models or multi-model setups.

Best Value

40GB when memory isn't the constraint — same compute at lower cost.

Frequently Asked Questions

Is the A100 80GB faster than the 40GB?

No — both have identical compute performance at 312 FP16 TFLOPS. The 80GB version only provides more memory, not more speed.

Which A100 should I choose?

If your model fits in 40GB of VRAM with room for batch data, choose the 40GB to save cost. If you need more memory for larger models or bigger batches, the 80GB is worth the 25-35% premium.