AI development today is fragmented. You have dozens of Large Language Models (LLMs), different APIs, different pricing models, and a never-ending list of configurations. Developers often spend more time juggling providers and infrastructure than actually building.
That’s why we built PureRouter, an AI Router designed to simplify AI orchestration. With PureRouter, you can connect, test, deploy, and optimize models without the complexity of manual DevOps or vendor lock-in.
What is AI Routing?
Why does PureRouter exist?
Why use an AI Router?
How does PureRouter handle model orchestration?
If you’ve ever asked yourself “Which model should I use?”, or wasted hours switching between providers, the answer is: use an AI Router.
PureRouter offers:
Integrate LLMs from multiple providers (OpenAI, Anthropic, Gemini, Mistral, DeepSeek, and more).
Route queries to the most affordable models without sacrificing quality.
Deploy open-source models on demand with auto-scaling infrastructure.
See the cost, latency, and quality tradeoffs for every query.
Let’s break down the PureRouter console step by step.
The Playground is where experimentation begins.
Select multiple models.
Choose a Response Mode: Economy, Balanced, or Quality.
Submit your query.
The Playground returns:
Model responses (side by side).
Response time.
Cost per request.
This makes it easy to evaluate which LLM best fits your use case, whether you’re optimizing for speed, price, or accuracy.
PureRouter already supports a large and growing collection of models, from OpenAI GPT-4, GPT-4o, GPT-3.5, to Anthropic Claude, Gemini, Mistral, DeepSeek, Qwen, Gemma, LLaMA, and more.
For the full and constantly updated list, check our Supported Models Documentation
Easily connect your accounts across top LLM providers:
This makes it easy to evaluate which LLM best fits your use case, whether you’re optimizing for speed, price, or accuracy.
PureRouter already supports a large and growing collection of models, from OpenAI GPT-4, GPT-4o, GPT-3.5, to Anthropic Claude, Gemini, Mistral, DeepSeek, Qwen, Gemma, LLaMA, and more.
For the full and constantly updated list, check our Supported Models Documentation
PureRouter isn’t just about routing hosted APIs. You can deploy your own open-source models in minutes.
Deployment steps:
All deployments come with secure connections, access controls, and auto-scaling.
Easily generate and manage multiple API keys for your projects.
Create separate keys for different teams or environments.
Revoke, rotate, and monitor usage.
No subscriptions. No hidden fees. PureRouter uses credits to keep billing simple:
Machine time: billed per hour for deployments.
Per-inference routing: billed per model call, starting as low as 0.001 credits per inference.
How credits are calculated?
Credits are our internal unit. You only pay for what you use.
Every new user gets $10 free credits (no credit card required) to test deployments and routing, use the code WELCOME10.
Comprehensive docs cover everything from quickstart guides to advanced deployment configurations.
The Optimized AI Stack You’ve Been Waiting For
PureRouter combines:
AI routing (query orchestration across models)
Open-source model deployments
Transparent billing
Simple integrations
Whether you’re building AI apps, experimenting with LLMs, or scaling production workloads, PureRouter is your AI orchestration layer, without the complexity.