The Real Size of AI Frameworks: A Wake-Up Call

You Think You Know What You're Installing When someone says "just install PyTorch," you probably think "how bad can it be?" It's a deep learning library, right? A few hundred megabytes, maybe? Think again. I built pip-size to expose the hidden cost of Python packages. And what I found in the AI ecosystem is... shocking. The Numbers Don't Lie I ran pip-size on the most popular AI frameworks. Here are the results: Framework Package Size Total (with deps) torch 506.0 MB 2.5 GB 🤯 tensorflow 545.9 MB 611.9 MB paddlepaddle 185.8 MB 212.1 MB jax 3.0 MB 137.1 MB onnxruntime 16.4 MB 39.5 MB transformers 9.8 MB 38.4 MB keras 1.6 MB 29.5 MB The PyTorch Surprise Here's what happens when you pip install torch: torch==2.11.0 506.0 MB (total: 2.5 GB) ├── nvidia-cudnn-cu13==9.19.0.56 349.1 MB ├── nvidia-cublas==13.3.0.5 384.6 MB [extra: cublas] ├── nvidia-nccl-cu13==2.28.9 187.4 MB ├── triton==3.6.0 179.5 MB ├── nvidia-cusparse==12.7.9.17 143.9 MB [extra: cusparse] ├── nvidia-cusparselt-cu13==0.8.0 1