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Subquadratic Raises $29.0M Seed Round

Recently funded · $29.0M SeedTechnology, Information and MediaUSView source

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Subquadratic, an AI lab dedicated to advancing the next frontier of large language models, has successfully closed a $29.0M seed funding round.

This significant early-stage capital infusion will empower the company to accelerate its work leading the subquadratic LLM revolution, a critical area focused on developing more efficient and scalable AI models. The investment underscores a strong belief in Subquadratic's foundational research and its potential to reshape the future of artificial intelligence by making complex AI applications more accessible and performant.

From the source

Andrew · May 5, 2026

The "Transformer Tax" just went to zero. Standard LLMs are hit with a "Quadratic Penalty"—the more you feed them, the slower and more expensive they get (O(n^2)).  Subquadratic just launched with $29M in seed funding to solve this.

Their new model, SubQ, is the first built on a fully sub-quadratic sparse-attention architecture (SSA). It’s not just a faster model; it’s a new infrastructure for "Deep Context." Here is the 5-point breakdown of the SubQ breakthrough: 1. The 12 Million Token Horizon 🧵 Most frontier models (Claude, Gemini) hit a wall at 1M–2M tokens. SubQ handles 12 million. That’s 120 books, an entire codebase

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