Post by Subquadratic

The transformer architecture used for ChatGPT, Gemini, and Claude has defined the last decade of AI. It also introduced a fundamental constraint: compute scales quadratically as context grows. Longer inputs, exponentially higher costs and accuracy that degrades well before the context window limit. SubQ changes that. It's the first LLM that breaks the quadratic scaling constraint delivering longer context, frontier level accuracy, and lower cost at the same time without tradeoffs. Read more here.