About ModelOpt

AI model recommendations with transparent logic

ModelOpt helps developers and teams pick the right model for local and cloud inference. We combine deterministic hardware filtering with Gemini-assisted recommendation reasoning.

Mission

Remove guesswork from AI model selection and make local AI accessible for every hardware tier.

How ModelOpt Works

1. Validate GPU, RAM, VRAM, use-case, and preference inputs.

2. Filter models based on compatibility rules.

3. Rank candidates with speed/quality bias.

4. Generate final recommendation narrative with Gemini.

Data Transparency

Model metadata includes cited sources, context windows, quantization support, and conservative throughput estimates.

Update Cadence

Data is refreshed continuously as new open models, benchmarks, and hardware profiles are released.

Tech Stack

Next.js 14, TypeScript, Tailwind, ShadCN UI, Zod, React Hook Form, and Vercel serverless APIs.

Created by Mohan Prasath

Hi, I am Mohan Prasath, a full-stack AI engineer focused on practical developer tools and production-grade AI systems.

Professional updates and community posts.

GitHub

Open-source projects, experiments, and releases.

Website

Portfolio, writing, and technical work.