Token Cut for AI Productivity

Cut LLM Token Costs With Jev Model Routing

Token Cut is an intelligent AI model routing platform designed to help developers reduce LLM and generative AI costs without sacrificing the quality of their applications.

Instead of sending every request to the same expensive model, Token Cut analyzes each task and automatically routes it to the lowest-cost model capable of handling it well.

At the core of Token Cut is Jev, a lightweight decision model that evaluates incoming requests and determines how much model capability they actually require. A simple question, translation, classification, or data extraction task can be routed to an inexpensive model, while coding, complex reasoning, and other demanding tasks can automatically use more capable models.

The idea is simple: don’t use the most powerful model for every request — use the right model for each task.

Token Cut evaluates multiple factors when making routing decisions, including task type, model capability, modality, context requirements, pricing, budget, and routing confidence.

It also works across multiple AI providers and model platforms, including OpenRouter, , Replicate, , and others. This gives developers access to a much larger pool of models without having to manually compare providers, maintain complicated routing logic, or constantly update application code as new models and prices appear.

With Token Cut, developers can use one API while the routing layer handles model selection behind the scenes.

Unlike traditional LLM cost monitoring tools that tell you how much money you already spent, Token Cut focuses on optimizing costs before the API request happens. If a cheaper model can reliably complete a task, there is little reason to send the same request to a model that costs 10x, 20x, or even more.

Token Cut is built around several core capabilities:

• Intelligent task classification powered by Jev• Automatic model selection and cost-based routing• Support for text, image, video, and audio models• Multi-provider routing across major AI platforms• Model capability, context, budget, and pricing evaluation• One API for accessing and routing across different models• Cost estimation and savings analysis• Automatic escalation to stronger models when tasks require more capability

The goal isn’t simply to use the cheapest AI models. It’s to eliminate unnecessary spending while maintaining the level of quality each task requires.

Token Cut turns model selection from something developers have to constantly manage into an infrastructure decision that can happen automatically.

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