VultronRetriever family of models released on HuggingFace![R]

Highlights

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 🔧

Model Links

• 🏆 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

Resources

• 📊 MTEB Leaderboard: https://mteb-leaderboard.hf.space/benchmark/ViDoRe(v3)
• 🐍 Hydra Architecture: https://arxiv.org/abs/2603.28554