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On October 29, Kakao open-sourced two Korean-optimized embedding models on Hugging Face: Kanana-2-3b-embedding (3 billion parameters) and Kanana-2-1.3b-embedding (1.3 billion parameters), targeting personalized AI agents and RAG scenarios. Kakao said that in internal evaluations, the two models outperformed llama-nemotron-embed-1b-v2 and Qwen3-Embedding-4B of comparable scale in Korean retrieval performance, with comparable English performance and higher inference efficiency, while memory usage and inference speed improved by more than tenfold compared with the previous-generation Kanana embedding models. The models adopt MRL, allowing developers to adjust the embedding vector size, and are released under the Kanana Open License for commercial use. There are currently no further developments.
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Kakao Open-Sources Two Korean-Optimized AI Search Embedding Models on Hugging FaceDevelopments
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- Source:The Elec
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Oct 30
The Elec
Kakao Open-Sources Two Korean-Optimized AI Search Embedding Models on Hugging Face
On October 29, Kakao open-sourced two embedding models on Hugging Face, Kanana-2-3b-embedding (3 billion parameters) and Kanana-2-1.3b-embedding (1.3 billion parameters), targeting personalized AI agents and RAG scenarios. Kakao said that in internal evaluations, the two models outperformed llama-nemotron-embed-1b-v2 and Qwen3-Embedding-4B of comparable scale in Korean retrieval performance, with comparable English performance and higher inference efficiency, while memory usage and inference speed improved by more than tenfold compared with the previous-generation Kanana embedding models. The models use MRL to let developers adjust embedding vector size, and are released under the Kanana Open License, which permits commercial use.