Lucas Beyer praises figure separating base model gains from post-training gains
Overview
Lucas Beyer says a plot comparing final-model performance on non-post-trained tasks with performance on post-trained tasks shows improvement in the base model.
In an X post, he calls the figure evidence of a non-benchmaxxing approach and a big-model effect. The post quotes Muse Wonder, a new frontier model family from finkd for personal and professional agentic work. The report does not include the plot's data or any independent check of Beyer's reading.
Written by AI from the articles below · updated Oct 12, 2:48 PM ET
Check the sources:
Article timeline
The articles in this story. Times are ET.
Lucas Beyer (bl16)@giffmanaXLucas Beyer praises figure separating base model gains from post-training gainsAILucas Beyer says a plot comparing final-model performance on non-post-trained tasks with performance on post-trained tasks shows base model improvement. He calls it evidence of a non-benchmaxxing approach and a big-model effect. The post quotes Muse Wonder, a new frontier model family from finkd for personal and professional agentic work.

Heat trend
Not enough continuous observations to show a trend yet.