# Project export: ModelArena

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## Project metadata

- Hackathon: Cal Hacks 12.0
- Tagline: Stop guessing which AI model to use. Upload your dataset, test multiple models, and see which one actually performs best on your data.
- Devpost: https://devpost.com/software/modelarena
- GitHub: not linked
- Video: https://www.youtube.com/embed/28EpF4p2mE0?enablejsapi=1&hl=en_US&rel=0&start=&version=3&wmode=transparent
- Team: contributor stats unavailable

## Devpost submission (written by the team)

### Inspiration

We noticed developers and data teams spending hours testing different LLM APIs manually to find which model works best for their specific task. Generic benchmark scores don't reflect real-world performance on your actual data distribution. We built ModelArena to make this process systematic: upload your dataset once, test multiple models simultaneously, and get clear performance comparisons.

### What it does

ModelArena evaluates LLM models on your own dataset. Upload a CSV file with labeled data, select models to test (Llama, Mistral, Gemma, Qwen, etc.), run the evaluation, and view ranked results with accuracy scores and prediction details. This gives you objective metrics based on your specific data instead of relying on vendor claims or public benchmarks.

## README (from the GitHub repository)

No README available.

## Detected evidence (automated analysis)

No repository was indexed for this project. Claimed technologies below could not be checked against code.
- Next.js (technology) — claimed on Devpost, not found in the code
- React (technology) — claimed on Devpost, not found in the code
- Tailwind CSS (technology) — claimed on Devpost, not found in the code
- TypeScript (language) — claimed on Devpost, not found in the code

## Codebase structure

No repository index available.

## Key source files

No repository index available; no source files included.