The Jev Router is our most transparent router to date, and it benchmarks very well!
See how it picks the model in the Chatroom sidebar, including cache-aware cost tradeoffs:
You've never routed like this before.
@OpenRouter is bringing Jev to all of your LLM calls, so your agentic workflows never have to waste a token again.
As always, faster, cheaper, more intelligent. Go build the future.
Jev Router keeps a model that works for the rest of the session.
It can raise or lower effort without switching models. It switches only when the expected gain is larger than the cost, including the cached chat it would lose.
Jev reads the conversation text only to pick the model and effort.
It runs under zero data retention (ZDR) terms, so nothing is stored or trained on. Attachments are never sent to Jev, and requests with "zdr: true" work with Jev Router.
Jev Router runs on Jev, TypeSafe's first Decision / System One model.
Before each turn, Jev reads your prompt and scores it on difficulty and precision. Also checks whether a bigger model or more effort would help, whether a cheaper model is enough, and whether the task changed.
Most routers pick a model based on each message. Each switch loses the cached chat, so you pay full price for the new model to reread the whole conversation.
Most routers also route on the task type, not the difficulty. Easy and hard coding tasks get the same model.
Claude Opus 5.5 from @AnthropicAI is live on OpenRouter!
The first model in the Claude 5.5 family leads Opus 5 and Fable 5.1 on agentic coding, knowledge work, and computer use, with 1M context at $4/M input and $20/M output, 20% lower per token than Opus 5.
Grok 4.7 from @SpaceXAI is live on OpenRouter!
Their most capable model for coding and knowledge work. It works longer on hard tasks, checks its own work more carefully, and sits at the frontier of price-performance on CursorBench 4.0.
Use it now: