RouteLLM: How I Route to The Best Model to Cut API Costs

Author(s): Gao Dalie (高達烈)

Originally published on Towards AI.

large language models have shown amazing capabilities in a variety of tasks, but there is a big difference in their cost and capabilities.

Claude 3 Opus, GPT-4, and others are high in performance, but they are also high in cost. So that’s why we’re making deals now. The trade-off is: use the best, brightest, and most expensive, or go for something cheaper, faster, and less capable.

But what if there was a better way? This leads to the dilemma of deploying LLMs in the real world.

if you’re building something to run a business or help with web research, whatever you’re doing with these models, routing all your queries to the biggest, most capable model will give you the highest quality responses, but it can be costly.

some of these projects are blowing thousands of dollars because they’re all relying on GPT-4 or whatever

Of course, you can save money by routing queries to smaller models, but the quality of the responses can go down. GPT-3.5 is cheap, but the quality isn’t as good, and it fails on harder tasks

That’s where something like Route LLM comes in.

in this video, we will provide an easy-to-understand explanation of Route LLM, what it is, how it works, what… Read the full blog for free on Medium.

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Published via Towards AI