VultronRetriever family of models released on HuggingFace

Thrilled to announce the VultronRetriever family of models, which were announced during Raise Summit Paris and demonstrated running Q&A and embedding documents on the iPhone, fully offline! 📱 Some highlights from the VultronRetriever model family: 🥇 Each model ranks #1 in its respective class on the MTEB Leaderboard, with VultronRetrieverPrime-8B as the global #1 📦 VultronRetrieverPrime-8B has up to 16x smaller index storage footprint and 12x higher throughput versus previous 9B-class leaders 🎯 VultronRetrieverCore-4.5B ranks second only to Prime on the leaderboard, outperforming models twice its size ⚡ VultronRetrieverFlash-0.8B outperforms models up to 5x its size, runs cool on edge devices, and indexes up to 60 images per minute, fully offline! 🐍 Deploying the VultronRetriever models with the Hydra Architecture gives you late interaction retrieval at unparalleled precision, plus generation at up to half the memory of comparable models 🧪 All models were trained on datasets with 0% cross-dataset duplication and 0% eval contamination, and show no overfitting on privately run MTEB evals Grab them, break them, make them your own 🔧 🏆 Prime: https://huggingface.co/vultr/VultronRetrieverPrime-Qwen3.5-8B ⚙️ Core: https://huggingface.co/vultr/VultronRetrieverCore-Qwen3.5-4.5B ⚡ Flash: https://huggingface.co/vultr/VultronRetrieverFlash-Qwen3.5-0.8B 📊 MTEB Leaderboard: https://mteb-leaderboard.hf.space/benchmark/ViDoRe(v3)) 🐍 Hydra Architecture: https://arxiv.org/abs/2603.28554 submitted by /u/madkimchi [link] [Kommentare]