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LFM3 1.7b model praised for impressive speed and coherence

By PulseAugur Editorial · [2 sources] ·

The LFM3 1.7b model is being praised for its surprisingly strong capabilities despite its small size. Users have noted its impressive speed, with one benchmark showing over 20,000 tokens per second on a CUDA-enabled GPU. The model also demonstrates remarkable coherence, even with large prompt sizes up to 64k tokens, exceeding expectations for a 1.7 billion parameter model. AI

IMPACT Demonstrates that smaller, efficient models can achieve high performance, potentially lowering the barrier for local AI deployment.

RANK_REASON User reviews of a small language model.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LFM3 1.7b model praised for impressive speed and coherence

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User reviews of a small language model.
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2 independent sources
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model release, product
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COVERAGE [2]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Repulsive_Initial308 ·

    LFM3 1.7b - Rather good

    <!-- SC_OFF --><div class="md"><p>I finally got around to trying it. This tiny model is surprisingly capable it seems. Also tried the 2b VL - also very good but it has half the context of 1.7b.</p> <p>It's also quite fast:</p> <pre><code>$ llama-bench -m LFM3-1.7B-Q8_0.gguf -fa 1…

  2. r/LocalLLaMA TIER_1 English(EN) · /u/mumblerit ·

    LFM3-1.7b seems impressive

    <!-- SC_OFF --><div class="md"><p>Been testing Liquid's LFM3-1.7B (Q8_0 GGUF, llama.cpp, ROCm) as a candidate for compression and summarization work</p> <p>4.1k t/s prefill and ~78 t/s decode on a Strix Halo iGPU</p> <p>~7.1k / ~151 if you tensor-split it across a 7900 XTX + XT</…

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