How ModelIndex works

ModelIndex helps teams make AI model decisions by making tradeoffs explicit — from recommendation to real production cost.

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Step 1: Get a recommendation

Step 1

Tell us what you’re building

Start with your use case — chat, coding, RAG, analysis, or multimodal — to anchor recommendations in real workloads.

Step 2

Choose your tradeoff

Pick what matters most — quality, cost, speed, or context. We weight this strongly and still surface tradeoffs.

Step 3

Get a clear recommendation

One top pick plus strong alternatives, with plain-language reasons and known downsides.

Step 2: Understand real cost and risk

Picking a model is only the beginning. ModelIndex helps you understand how that choice behaves at scale — before surprises show up in production.

Cost simulator

Estimate monthly AI spend using realistic inputs like request volume, token sizes, retries, context usage, and traffic spikes.

See expected and worst-case cost — not just a single number.

Try the cost simulator →

Canonical scenarios

Opinionated, ModelIndex-authored examples of real AI workloads like customer support, internal copilots, and RAG search.

These show what typically works — and when it breaks.

View canonical scenarios →

Saved scenarios

Save cost simulations as named scenarios so you can return to them, share links, and reason about changes over time.

Scenarios are snapshots — reproducible and comparable.

Compare scenarios

Compare saved scenarios side-by-side to understand cost deltas, key drivers, and risk tradeoffs.

Answer “What if we chose this instead?” before committing.

What the fit score means

Fit scores are directional (1–10). They reflect how well a model matches your specific answers — not an absolute leaderboard.

9–10

Best match for your use case and constraints.

7–8

Strong match — great default choice.

5–6

Workable, but expect tradeoffs.

1–4

Not recommended for this scenario.

Data & transparency

Fit scores are directional and relative within a curated set. We weigh use-case fit most, then your stated priority (quality/cost/speed/context), then reliability for production. Scores are not exhaustive benchmarks.

Sources we reference

• Provider pricing pages
• Provider model docs / context windows
• Release notes / model cards (when available)

Model data last updated: 2026-01-03

Ready to explore your options?

Start with a recommendation, then understand the real cost before you ship.

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