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Laya leads local decision model speed tests on RTX 4090

By PulseAugur Editorial · [1 sources] ·

A recent benchmark test evaluated four open decision models—Laya, d1, Clef-Flash, and Lev—on an RTX 4090 GPU to determine their local performance. The test involved reading nine Wikipedia articles about centipedes and identifying specific terms. Laya emerged as the fastest model, processing words at 3.9 ms per word and achieving 7,980 words in 32 seconds. While Lev demonstrated the highest accuracy in catching centipede names, it was significantly slower, taking 51.0 ms per word. AI

IMPACT Laya's speed advantage suggests it could be a preferred choice for applications requiring rapid local processing of decision models.

RANK_REASON Benchmark results for open decision models. [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 →

Laya leads local decision model speed tests on RTX 4090

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Benchmark results for open decision models. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Fun-Meaning-6474 ·

    Running decision model locally on an RTX 4090 to find out which one is the fastest

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1x0wg85/running_decision_model_locally_on_an_rtx_4090_to/"> <img alt="Running decision model locally on an RTX 4090 to find out which one is the fastest" src="https://external-preview.redd.it/M2F5N2Q4NHl5OXVoM…

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