DEV Community

Adipta Martulandi
Adipta Martulandi

Posted on

Use this Technique to Reduce LLMs Cost by Over 50%

Large Language Models (LLMs) have revolutionized the way we interact with and utilize artificial intelligence. From generating text to answering complex questions, their versatility is unmatched. However, this power comes at a significant cost — API usage, measured in tokens, can quickly escalate, making these solutions prohibitively expensive for many individuals and organizations.

Reducing token usage while maintaining output quality is a crucial challenge for making LLMs more accessible and affordable. This is where prompt compression comes into play. By strategically shortening input prompts, we can drastically cut costs without compromising the quality or fidelity of the model’s responses.

In this article, we’ll explore LLMLingua-2, a novel method for efficient and faithful task-agnostic prompt compression. Developed by researchers at Microsoft, LLMLingua-2 leverages data distillation to learn compression targets, offering a robust approach to minimize token usage while preserving performance across various tasks.

Full Article Here

Image of Timescale

Timescale – the developer's data platform for modern apps, built on PostgreSQL

Timescale Cloud is PostgreSQL optimized for speed, scale, and performance. Over 3 million IoT, AI, crypto, and dev tool apps are powered by Timescale. Try it free today! No credit card required.

Try free

Top comments (0)

Billboard image

The Next Generation Developer Platform

Coherence is the first Platform-as-a-Service you can control. Unlike "black-box" platforms that are opinionated about the infra you can deploy, Coherence is powered by CNC, the open-source IaC framework, which offers limitless customization.

Learn more

👋 Kindness is contagious

Please leave a ❤️ or a friendly comment on this post if you found it helpful!

Okay