Best LLM Routers and Model Routing Tools in 2026

LLM routers aim to reduce AI coding costs without sacrificing completed-task quality by selecting models per request based on predicted difficulty, cost, speed, or availability, while gateways generally rely on configurable rules, retries, fallbacks, and provider health rather than quality prediction. The comparison distinguishes learned routing products such as Weave Router, Cursor Router, RouteLLM, Not Diamond, Microsoft Foundry Model Router, and Amazon Bedrock Intelligent Prompt Routing from rule-based platforms including LiteLLM and Portkey, while noting that documentation and independently verified performance data vary widely. Weave Router is presented as suited to multi-tool engineering teams because it routes individual coding actions across supported providers and links decisions to code quality, pull-request outcomes, and cost per merged pull request, although its reported results are vendor supplied and its license is source-available rather than conventionally open source. Cursor Router is positioned for organizations using Cursor exclusively, OpenRouter and LiteLLM for broad provider access, RouteLLM for teams building and evaluating their own strong-versus-weak model selectors, Portkey for enterprise gateway controls, and Foundry and Bedrock for Azure- and AWS-centered deployments. Key purchasing considerations include routing granularity, selection method, model-pool breadth, session and cache awareness, telemetry, deployment control, security, and whether lower token spending actually reduces retries and improves software-delivery outcomes.

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