AI Token Router vs OpenRouter: how to choose
Both are solid options. Here’s how they actually differ, so you can pick the right one for your use case.
OpenRouter: The unified router across every model, open and closed. · Of the 8 dimensions below, OpenRouter wins 3.
Model catalog size
AI Token Router
7 open-weight models callable now, 24 catalogued
OpenRouter
500+ models across 80+ providers
Closed frontier models (GPT, Claude, Gemini)
AI Token Router
Not offered — open weights only
OpenRouter
Yes, with automatic fallback routing
Platform fee
AI Token Router
None
OpenRouter
~5.5% on credit purchases (non-crypto)
Video model support
AI Token Router
Yes — dedicated category, 6 models, published per-second rates
OpenRouter
No
Cached-input pricing visibility
AI Token Router
Dedicated column on every pricing row
OpenRouter
Varies by upstream provider; not surfaced uniformly
Gateway overhead
AI Token Router
Direct to our own inference, no routing hop
OpenRouter
~25–40ms documented routing overhead
Provider redundancy
AI Token Router
Single-provider per model
OpenRouter
Multi-provider failover per model
Spending caps
AI Token Router
Per account and per key, at signup
OpenRouter
Credit-balance limited
Figures reflect each provider’s published information as of September 2026. If something here is out of date, tell us and we’ll correct it — including in OpenRouter’s favour.
When you should choose OpenRouter
If you need broad access to closed-source frontier models — GPT, Claude, Gemini — alongside open ones, all through a single router with automatic provider fallback, OpenRouter is genuinely the better fit. That is not what we are built for, and a router with 500 models and multi-provider redundancy solves a real problem that our 22-model catalog does not. If your architecture depends on failing over between providers when one degrades, choose them.
When you should choose us
If you are specifically working with open-weight models and want the lowest total cost with fully published pricing — no platform fee on top, cached input visible before you commit, and video models treated as a real category rather than something we do not carry — that is exactly what we built this for.