---
title: "nnzen model catalog"
url: "https://ramenm.com/en/projects/llm-models-hub"
markdown_url: "https://ramenm.com/en/projects/llm-models-hub/index.md"
locale: "en"
content_language: "en"
page_kind: "project"
source: "localized_path"
llms_url: "https://ramenm.com/llms.txt"
llms_full_url: "https://ramenm.com/llms-full.txt"
---

# nnzen model catalog

- Case study URL: https://ramenm.com/en/projects/llm-models-hub
- Markdown URL: https://ramenm.com/en/projects/llm-models-hub/index.md
- Role: Founder / Backend Developer
- Period: 2025-2026
- Team: Solo

A live LLM catalog that collects model data, normalizes it, and makes model comparison faster.

## Problem
Model data was scattered across sources, so pricing, context size, limits, and quality signals had to be checked by hand.

## Solution
Built a FastAPI backend for OpenRouter ingest, normalized model cards, ranking context, and search/filters over one consistent shape.

## Impact
Model research moved from tabs and notes into one searchable comparison surface.

## Stack
- Python, FastAPI, LLM APIs, RAG, Vector DB / pgvector, Tool calling

## Metrics
- Catalog: 500+ model records
- Data flow: Normalized ingest
- Surface: Live product

## Highlights
- Built ingestion and normalization for model catalog data.
- Exposed search, filters, and comparison context for faster model selection.
- Kept the backend extensible for new model sources and ranking signals.

## Lessons
- Good data tools need boring normalization before they need a fancy UI.
- Decision speed matters more than showing every possible detail at once.

## Links
- [Open nnzen.com](https://nnzen.com)