Most teams pick a model by reputation, then never revisit it. Cortega's Model Recommender ranks a curated catalog of models against your actual workload, team size, and priorities, with public benchmark evidence behind every result, and shows cost, quality, and performance versus the model you run today.
Defaulting to whatever model is trending skips the only questions that actually matter for your deployment: what you're using it for, how many people it serves, and what you're already paying. The Model Recommender starts from those instead.
Free and self-serve. Tell it what you're doing, how much of it, and what matters most, and it ranks the catalog accordingly.
Pick the workloads you run and the number of people they serve.
Requests per month, input and output tokens per request, pre-filled from your workloads and editable if you have measured traffic.
Optionally name the model you already run. Recommendations must meet or beat it on capability, scored against it directly.
Weight what matters most: quality, cost, coding, reasoning, chat, speed, or tool use.
The Model Recommender draws on the same model intelligence Cortega uses elsewhere in the platform. Pick a model here, then configure it as a routing target in your gateway.
Results are backed by public benchmark evidence, so a ranking is something you can check, not a black-box score.
Once you know which models fit, configure them in Cortega's weighted, failover, or conditional routing strategies, enforced at the gateway.
No sales pitch — just an email when a new model, price change, or benchmark shifts the rankings for the workload types you care about.
Tell us what you're running today and what you're trying to optimize for, and we'll walk through the recommendation with you.