Model Complexity Estimator

Estimate FLOPs, memory usage, and inference time for neural networks

Model Architecture

e.g., 224 for ImageNet models
Total depth of network
Model weight count in millions
For inference time estimation

Complexity Metrics

FLOPs (Forward Pass)
—
Memory Usage (Inference)
—
Inference Time (Single Sample)
—
Throughput (Samples/sec)
— samples/sec
Parameter Memory
— MB

Architecture Comparison

Metric Value Estimate
Peak GPU Memory —
Total Parameters — Millions
Depth — Layers
Compute Efficiency — FLOPs/Parameter
Batch Throughput — Samples/sec

FLOPs vs Memory Trade-off