mLateOn wins HAKARI-Bench by 8.33 points with a quarter of runner-up's active params
IgorCarron · x · 2026-08-20
HAKARI-Bench creator @hotchpotch reports that LightOn's mLateOn tops all 11 evaluated late-interaction retrievers: 65.52 Overall Macro, 8.33 points above runner-up pplx-embed-v1-late-0.6b (57.19), with only 115.1M active parameters versus 440.6M. With 312M total params, it scores 63.33 on MNanoBEIR — in the same tier as 8B dense models like Qwen3-Embedding-8B and Nemotron-3-Embed-8B. It supports 8,192-token inputs, reusable document encodings for reranking, and stays top-tier on English retrieval.
Related event: LightOn's mLateOn Tops Multilingual ColBERT Retrieval Benchmark(2 posts)→
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