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Subquadratic launches 12M-token LLM, claims major architectural shift

By PulseAugur Editorial · [1 sources] ·

Subquadratic, a Miami-based startup, has emerged from stealth claiming to have developed the first Large Language Model (LLM) that does not utilize quadratic attention. This architectural innovation reportedly enables the model to process a context window of 12 million tokens at a significantly reduced cost compared to existing frontier models. AI

IMPACT Potential to drastically lower inference costs for LLMs with extremely long context windows.

RANK_REASON Startup announces a novel LLM architecture with a large context window and reduced cost. [lever_c_demoted from significant: ic=1 ai=1.0]

Read on Mastodon — fosstodon.org →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Subquadratic launches 12M-token LLM, claims major architectural shift

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Startup announces a novel LLM architecture with a large context window and reduced cost. [lever_c_demoted from significant: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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model release, paper
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High
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141 days old
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COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    A Miami-based startup called Subquadratic came out of stealth last week with a single claim that’s either the most important architectural shift since the 2017

    A Miami-based startup called Subquadratic came out of stealth last week with a single claim that’s either the most important architectural shift since the 2017 transformer paper or the most sophisticated AI hype in recent memory. They say they’ve built the first LLM that doesn’t …

    LINKS firethering.com/subq-12m-token-context-ll…

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