LLM Fine-Tuning (LoRA vs. Full Parameter) Solver

Underwrite parameter-efficient fine-tuning (PEFT), ranking rank adapters (r=16/64), GPU hours (NVIDIA A100/H100 80GB), and slashing model training compute bills by 85%.

Dataset Tokens & Model Parameter Size

Fine-Tuning Dataset Tokens (Millions - e.g. 50M)

Base Model Size (Billions - 8B, 14B, 70B)

Training Epochs (e.g. 3 Epochs)

GPU Hours & Training Bills

QLoRA / LoRA GPU Compute Bill (8x A100)

$365.40 Total Training

Full Parameter Training Compute Bill (32x H100)

$2,850.00 Total Training

Compute Cost Reduction

LoRA Slashes -87.2% Compute Spend