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Model Intelligence

Model Intelligence is a curated, weekly-refreshed catalog of LLM quality, cost, and speed data, built from public benchmark sources: models.dev, OpenRouter, LMSYS Arena, LiveBench, Aider, SWE-bench, and others. It ranks models against your workloads and usage, with the benchmark evidence for each recommendation attached.

Free to use standalone at modelint.cortega.ai, no Cortega install required. Also available as a plugin on AI Border Gateway.

The problem it solves​

A model you depend on can be deprecated or superseded with little warning. Picking a replacement by hand means re-checking benchmark leaderboards and pricing pages every time. This is as much an AI governance problem as routing or access control: see The AI governance problem.

Standalone: modelint.cortega.ai​

Pick your workloads (employee assistant, customer chatbot, coding assist, document Q&A, and others), enter usage volume, and move quality, cost, and speed weight sliders. The tool ranks the current catalog (2,100+ models at last count) and returns, for each candidate: the benchmark scores behind the ranking (Arena Elo, BenchLM, LiveBench, and others), and estimated monthly cost across multiple sellers, GPU rental, and reserved-instance options.

As a plugin on AI Border Gateway​

The same ranking engine runs against your actual traffic pattern and usage volume instead of a manually entered estimate. It appears in AI Border Gateway's Insights, under Recommendations:

  • Discover. Rank the full catalog against your real workloads and usage.
  • Upgrade. Check your currently configured models against the catalog. A model that's been deprecated or superseded comes back with a named successor, not just a warning.

The Workload Analyzer agent is what turns this into a running recommendation: it classifies your traffic into workload categories, and feeds that classification and your usage volume into Model Intelligence's ranking.

Where it connects to other Cortega features​

The same catalog also supplies the workload-category taxonomy Workload Analyzer uses to classify traffic in the first place. Two integration points, one underlying dataset.