OrcaRouter
AI API router optimizing spend by dynamically routing prompts based on difficulty
Score
60
User Rating
3.0
Free/Trial Support
Not Supported
Starting Price
--
Last Updated
Aug 14, 2026
Overview
What is OrcaRouter?
OrcaRouter is an AI API gateway and multi-model LLM router that dynamically routes user prompts to the most cost-effective and appropriate model across OpenAI, Anthropic, Gemini, and over 200 other models. By instantly grading every prompt for difficulty, OrcaRouter directs complex reasoning tasks to frontier models while routing routine requests to cheaper, open-source alternatives. This process allows developers to slash their AI spending by approximately 40% while preserving high-quality results. It features an OpenAI-compatible API, meaning integration requires changing just a single line of code to swap the base URL and API key. OrcaRouter provides transparent 'glass-box' routing by logging the difficulty grade, model selection, and provider for each request with zero token markup, passing the original provider costs directly to the user.
What is OrcaRouter used for?
Tags
Top Features
- Quality-graded routing that automatically dynamically shifts traffic based on prompt difficulty
- OpenAI-compatible single-line migration using existing SDKs and streaming formats
- Automatic transparent failover to prevent service errors if an upstream provider goes down
- Zero token markup passing exact published developer rates directly from first-party providers
- Glass-box per-request route attribution showing exact difficulty grades and chosen providers
- Granular team budget enforcement with hard and soft spending limits, allowlists, and rate limits
How to use OrcaRouter?
To use OrcaRouter, point your existing OpenAI or LLM SDK to the new base URL (https://api.orcarouter.ai/v1) and substitute your current API key with an OrcaRouter API key. Set your model parameter to 'orcarouter/auto' in your code, and the gateway will automatically grade and route your prompts.
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Use Cases
- Reduce multi-model LLM inference costs across a tech stack by 40% without compromising on response quality
- Build resilient production applications with automated failover handling across diverse cloud AI providers
- Manage internal company or team-wide AI spending, API access keys, and model permissions from a single dashboard
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