ConfigIQ

LLM inference sizing, GPU comparison, and cost modeling for engineers and infrastructure teams.

Live at configiq.dev

Built with Next.js + PatternFly, powered by AIConfigurator.

What it does

Tool	Description
Quick Estimate	Fast GPU memory and cost estimate from model + load profile
Advanced Calculator	Detailed sizing with batching, quantization, and cost modeling
KV Cache Calculator	Memory breakdown and KV cache capacity analysis
GPU Explorer	Compare GPUs across memory, throughput, cost, and availability
Hybrid Savings	Model cost savings across cloud, on-premise, and hybrid strategies
Routing Economics	Analyze request routing between model tiers

Getting started

Prerequisites

• Node.js >= 20
• npm >= 10

Setup

git clone https://github.com/openshift-psap/configiq.git
cd configiq
npm install
cp .env.example .env.local
npm run dev

App runs at http://localhost:3000.

Available commands

npm run dev          # Start dev server (http://localhost:3000)
npm run build        # Production build
npm run type-check   # TypeScript check without building
npm run lint         # ESLint

Tech stack

Layer	Technology
Framework	Next.js 14 App Router + TypeScript
UI	PatternFly v5
Backend API	AIConfigurator (GPU sizing + memory estimation)
Deployment	Vercel

Project structure

app/                  Next.js App Router pages
  layout.tsx          Root layout, fonts, PatternFly CSS imports
  page.tsx            Homepage
  quick-estimate/     Quick Estimate tool
  calculator/         Advanced Calculator
  kv-cache/           KV Cache Calculator
  gpu-explorer/       GPU Explorer
  hybrid-savings/     Hybrid Savings
  routing/            Routing Economics
  api/                Next.js API routes (proxy to AIConfigurator)
    recommend/        POST — GPU sizing via AIC /recommend
    memory/           POST — memory breakdown via AIC /memory
    gpus/             GET — GPU catalog
    models/           GET — model catalog
components/
  layout/
    AppShell.tsx      Top-nav masthead + sidebar navigation
lib/
  gpu-math/           GPU sizing formulas (client-side)
  api/                AIConfigurator API clients
  pricing/            Cloud GPU pricing data
docs/                 Architecture docs and ADRs

Contributing

Before opening a PR

CI runs automatically and must pass:

npm run type-check   # Must be clean
npm run lint         # Must be clean
npm run build        # Must succeed

Code conventions

1. GPU math belongs in lib/gpu-math/ — never write sizing formulas inside React components.
2. PatternFly only — do not add Tailwind, shadcn/ui, or any other component library.
3. Sentence case everywhere — no title case in headings or labels.
4. Server components by default — add "use client" only when needed.
5. No any types — TypeScript strict mode is enforced.