Small LLMs stay competitive on short transcripts, then fade at meeting length

AssemblyAI said its benchmark data shows small language models can match larger systems closely on short voice transcripts, but lose that edge as transcript length increases. In its Voice Standard Bench run published Oct. 13, 2026, the company said the performance gap widens on longer meetings, while the cost advantage of smaller models narrows once the task becomes more complex. The post, published Oct. 20, 2026, frames the question as one of transcript length rather than model class alone.

Source: Blockchain.News