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Basalt engine leads in Qwen3.8-FN inference speed tests

A comparison of three inference engines—basalt, cachy-flash, and ninfer-ext—for the Qwen3.8-FN model on an NVIDIA RTX 5090 GPU revealed that basalt generally offered superior performance. Across various context lengths, basalt consistently achieved higher tokens-per-second rates for both prefill and decoding operations. While cachy-flash showed competitive prefill speeds at shorter contexts, basalt maintained its lead as context length increased, and ninfer-ext lagged behind both. AI

IMPACT Optimizing inference engines can significantly improve the speed and efficiency of running large language models locally.

RANK_REASON Benchmark comparison of inference engines for a specific model. [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 →

Basalt engine leads in Qwen3.8-FN inference speed tests

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Benchmark comparison of inference engines for a specific model. [lever_c_demoted from research: ic=1 ai=1.0]
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High
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1 days old
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COVERAGE [1]

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

    Qwen3.8-FN at NVFP4 ( Basalt vs cachy-flash vs ninfer-ext)

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1xcp0mf/qwen38fn_at_nvfp4_basalt_vs_cachyflash_vs/"> <img alt="Qwen3.8-FN at NVFP4 ( Basalt vs cachy-flash vs ninfer-ext)" src="https://preview.redd.it/t60qh98nz1xh1.png?width=640&amp;crop=smart&amp;auto=webp&…