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Tiny 1.6MB model plays Connect Four with 1.375 bits/weight

By PulseAugur Editorial · [1 sources] ·

Precisit has developed a 1.6 MB model that plays Connect Four with performance comparable to its 7.8 MB int8 version. This new model utilizes Sherry's 3:4 ternary format, achieving 1.375 bits per weight, and runs efficiently in a browser via WebGPU. The research indicates that training with this format is crucial for optimal performance, as post-training conversion significantly degraded the model's capabilities. AI

IMPACT Demonstrates significant model compression techniques applicable to LLMs, enabling smaller, more efficient deployments.

RANK_REASON Research paper detailing a new model format and its application. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

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

Tiny 1.6MB model plays Connect Four with 1.375 bits/weight

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3 / 100
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Newsworthiness bucket
Tool
Research paper detailing a new model format and its application. [lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
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.
Topics
model release, infra
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High
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Story freshness
Same-day
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Brilliant-Hall1387 ·

    Sherry's 3:4 ternary format (1.375 bits per weight) running on WebGPU: a 1.6 MB model that plays Connect Four as well as its 7.8 MB int8 version

    <!-- SC_OFF --><div class="md"><p>Not an LLM, but the ternary findings should carry over, and we hadn't seen Sherry-style 3:4 weights run in a browser before. Disclosure: this is our work at Precisit, everything is MIT.</p> <p><strong>What it is</strong></p> <ul> <li>A 7.4M-param…

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