239M multilingual embedder distilled from Qwen3-Embedding-4B onto an EuroBERT backbone.
A solid 0.212B-parameter dense embedding model from Jina AI. Treat the modality benchmarks above as the leading indicator of fit — composite scoring across modalities is still maturing.
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The lightweight (239M-parameter) sibling of jina-embeddings-v5-text-small, built on EuroBERT-210M and distilled from Qwen3-Embedding-4B with task-specific LoRA adapters and contrastive losses. Targets resource-constrained and edge deployments while still matching or exceeding all other sub-500M embedding models on MTEB and MMTEB.
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