# Echo: Fable-Level Performance with Open-Weight Models Boost AI performance while cutting costs by two-thirds. - **Source:** [Hacker News (news.ycombinator.com)](https://brifing.si/source/13c923cd-6d99-442b-9b8b-1181f4d8cd91) - **Published:** 2026-07-23 - **Topic:** [Data & AI](https://brifing.si/c/data-ai) - **Original article:** - **On Brifing:** https://brifing.si/s/d537b800-4d68-4eef-8e1e-7e012d9fd909 ## What is Echo? Echo is a project that combines multiple open-weight AI models into a single system. It aims to achieve higher performance by selecting the most suitable models for each task and merging their outputs. ## How Does It Work? Echo automatically determines how much computational power to allocate, which models to use, and how to combine their outputs for each request. This allows for better results with fewer resources in some tasks and collaboration of multiple models in others. ## Model Diversity Echo discovered the complementary features of different models. A model that appears weaker overall can be quite useful in specific tasks or combinations. ## Performance Comparison In initial evaluations, Echo outperformed the best individual model in its pool. It also achieved results close to a strong comparison system like Fable while reducing costs by two-thirds. ## Current Challenges Echo can sometimes make incorrect allocation or combination decisions. The developer is working to understand these errors and test whether the same approach holds for coding and agentic tasks. ## Try and Provide Feedback Echo offers a chat interface and an OpenAI-compatible API. Users are encouraged to test the system and report any issues they encounter. This feedback will help further improve the system. ## Sources covering this story - https://news.ycombinator.com/item?id=49026810 — --- _Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._