# Cosmos3 PhysicsIQ Reproduction End-to-end recipe for reproducing the PhysicsIQ benchmark with Cosmos3-Super using the native Cosmos Framework PyTorch entrypoint (`python -m cosmos_framework.scripts.inference`). The notebook walks through both PhysicsIQ task formats: - **Image-to-Video (I2V)**: condition on the single switch-frame JPG; generate 121 frames (1 conditioning + 120 generated); score the last 120. - **Video-to-Video (V2V)**: condition on a 3-second clip; pad the official 72-frame conditioning to 73 frames; generate 193 frames total; score frames 73..192. ## Files - `run_with_cosmos_framework.ipynb` — main notebook. - `assets/i2v_prompts.json` — 198 I2V upsampled prompts. - `assets/v2v_prompts.json` — 198 V2V upsampled prompts. ## Reference scores (Cosmos3-Super) | Task | PhysicsIQ score | | ---- | --------------: | | I2V | 43.8 | | V2V | 59.7 | ## Requirements - 4-GPU Linux node (configurable via `COSMOS3_NUM_GPUS`, default 4) - `uv == 0.11.29` - `ffmpeg`, `git`, `gcloud` (or `gsutil`) - Hugging Face access to the Cosmos3 model family