P-Bench / README.md
Minette Kaunismäki
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metadata
title: P-Bench
emoji: 🥇
colorFrom: green
colorTo: indigo
sdk: gradio
pinned: true
license: apache-2.0
short_description: A cost/quality/speed Leaderboard for Inference Providers!
sdk_version: 5.19.0
tags:
  - leaderboard

P-Bench

Compare text-to-image, text-to-video, image-to-video, and video-to-video models on quality, speed, and price. This repo is the Gradio dashboard: leaderboards, Pareto plots, and side-by-side samples.

The live Space is PrunaAI/P-Bench.

The current P-Video-2 Pro evaluation snapshots are data/t2v-pro.csv (text-to-video) and data/i2v-pro.csv (image-to-video). Both feed the leaderboards and price/time Pareto plots with Datapoint and Rapidata Elo. All models appear in the video-generation leaderboards, including variants with missing scores. Missing scores and ranks display as dashes; Pareto plots include only models with the required score and price or timing. Image-to-video sample media is not included in these exports. Rapidata Elo comes directly from these exports.

Run locally

From the repo root:

python -m venv .venv
source .venv/bin/activate
pip install "gradio==5.19.0" pandas -r requirements.txt
python app.py

requirements.txt lists Plotly. Gradio and pandas are required locally; Hugging Face Spaces installs Gradio from the YAML sdk_version above.

Deploy

origin is the Space (https://huggingface.co/spaces/PrunaAI/P-Bench). Publish the current branch to the live app with:

git push origin HEAD:main