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Mistral launches new code embedding model that outperforms OpenAI and Cohere in real-world retrieval tasks
Mistral's Codestral Embed will help make RAG use cases faster and find duplicate code segments using natural language.
“Codestral Embed can output embeddings with different dimensions and precisions, and the figure below illustrates the trade-offs between retrieval quality and storage costs,” Mistral said in a blog post. Embedding models generally target RAG use cases, as they can facilitate faster information retrieval for tasks or agentic processes. While it competes against more closed models, such as those from OpenAI and Cohere, Codestral Embed also faces open-source options from Qodo, including Qodo-Embed-1-1.5 B.
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