LoRA Parameter Count

Estimate trainable low-rank adaptation parameters for transformer projections.

How this calculator works

Enter layer input dimension, layer output dimension, lora rank, adapted projections, adapted layers. Select Calculate to apply the displayed formula and review the labeled results.

Formula / method

LoRA parameters = rank × (input dimension + output dimension) × projections × layers

Worked example

Rank 16 across four 4,096×4,096 projections in 32 layers adds about 16.8M trainable parameters.

Assumptions and limitations

Each adapted projection uses one rank-down and one rank-up matrix.

Biases, embeddings, convolutional adapters, mixed dimensions and checkpoint metadata are excluded.