We had to build new evals for Fable

What this post added

This post details the creation and application of new, more challenging evaluation benchmarks ('Frontier' eval set) for LLMs in data analysis contexts. It quantifies the performance improvements of Claude Fable 5 on these benchmarks, highlighting its superior analytical reasoning, ability to handle complex, long-horizon tasks, and better adherence to the 'golden workflow' of data analysis. The post also discusses qualitative improvements in how the model frames assumptions and communicates findings, contrasting it with previous models.