Practical guides to cutting your LLM costs with smart routing.
Learn how LLM routing works, why it matters, and how it can cut your AI costs by sending requests to the right model.
Understand how LLM pricing works — input tokens, output tokens, per-model rates — and where your money actually goes.
A side-by-side comparison of capabilities, cost, and latency to help you pick the right model for each task.
Actionable techniques — from prompt optimization to smart routing — that can cut your OpenAI bill immediately.
Token pricing tables, quality benchmarks, and use-case recommendations for choosing between Claude and GPT.
Real-world scenarios showing how a 10-person team can halve their LLM spend without sacrificing quality.
How to classify prompt complexity and automatically route to the cheapest model that can handle the job.
An architecture guide for running multiple LLM providers with abstraction layers, failover, and load balancing.
Pre-calculated tables showing costs at 1K to 1M requests/month across GPT-4o, Claude, Gemini, and more.
Pricing trends, open-source competition, and why smart routing becomes more valuable as models multiply.