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Zyphra introduces Hierarchical Attention (ZHA) for subquadratic attention
Briefing on ZHA, an attention method that searches a learned tree of compressed summaries, with speedups projected by the author over dense attention and over MSA at 10M tokens.
Zyphra announces Zyphra Hierarchical Attention (ZHA), an attention method that searches a learned tree of compressed summaries. According to the briefing dated 2 November 2026, the author projects speedups of 35 times over dense attention and 5 times over MSA at 10 million tokens. These figures are projections stated by the author, not results independently verified in the source text.
The material describes a subquadratic attention design, a direction engineers follow to make long-context processing more efficient. To consult the original, find Zyphra's article by the method name and date, then review the methodology, test sets and comparison conditions before citing the gains. Rota Nacional does not implement ZHA, and its relevance to your users is indirect. If you use AI to study this topic, do not paste sensitive documents or personal data into prompts.
Original source: Zyphra apresenta o Zyphra Hierarchical Attention para atenção subquadrática