Model Cost Simulator

Tune precision modes, quantization, and architectural overrides to see real-time impact on hardware limits, projected training time, and overall cloud costs.

Parameters (Millions)

Dataset Size (Tokens/Items)

Batch Size

Epochs

Primary GPU Instance

Compare GPU Hardware

Select a second GPU to directly compare training time and cost on the charts.

Distributed Data Parallel

Replicates model across GPUs. Splits batch.

Base Precision Mode

Mixed precision accelerates math and reduces VRAM dynamically (e.g., BF16, FP8 speedups). Shows exact impact to Optimizer states.

Quantization-Aware (QAT)

Simulates post-training quantization behavior. Drastically drops main weight VRAM footprint while keeping FP precision optimized.

Peak VRAM / GPU

67.8 GB

Max limit: 80 GB

Estimated Time

492.4 hrs

Projected Cost

$1,477.15

Saved $1,034.01 vs FP32

Model Cost Simulator

Base Model Config

Hardware & Scale

Advanced Features

Memory Allocation Details

Total Time Scaling (vs GPUS)

Cumulative Cost Comparison (Baseline FP32 vs Yours)