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 — so you always know why a model was chosen.

Mission

Remove guesswork from AI model selection and make local AI accessible for every hardware tier — from a 16GB laptop to a multi-GPU workstation.

How ModelOpt Works

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

Filter models based on hardware compatibility rules.

Rank candidates with speed/quality bias weighting.

Generate final recommendation narrative with Gemini.

Our Principles

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.

Privacy First

No server-side storage of your inputs. All session data stays in your browser and is cleared when you close the tab.

Tech Stack

Next.js 14TypeScriptTailwind CSSReact BitsFramer MotionGemini AIZodReact Hook Form

Creator

Built by Mohan Prasath

Hi, I'm Mohan Prasath — a full-stack AI engineer focused on practical developer tools and production-grade AI systems. I'm currently studying at B.S.A. Crescent Institute and building projects at the intersection of LLMs, developer tooling, and hardware constraints.

Professional updates and community posts.

GitHub

Open-source projects, experiments, and releases.

Website

Portfolio, writing, and technical work.