Compare the Top Embedding Models that integrate with Mistral AI as of October 2025

This a list of Embedding Models that integrate with Mistral AI. Use the filters on the left to add additional filters for products that have integrations with Mistral AI. View the products that work with Mistral AI in the table below.

What are Embedding Models for Mistral AI?

Embedding models, accessible via APIs, transform data such as text or images into numerical vector representations that capture semantic relationships. These vectors facilitate efficient similarity searches, clustering, and various AI-driven tasks by positioning related concepts closer together in a continuous space. By preserving contextual meaning, embedding models and embedding APIs help machines understand relationships between words, objects, or other entities. They play a crucial role in enhancing search relevance, recommendation systems, and natural language processing applications. Compare and read user reviews of the best Embedding Models for Mistral AI currently available using the table below. This list is updated regularly.

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    Codestral Embed
    Codestral Embed is Mistral AI's first embedding model, specialized for code, optimized for high-performance code retrieval and semantic understanding. It significantly outperforms leading code embedders in the market today, such as Voyage Code 3, Cohere Embed v4.0, and OpenAI’s large embedding model. Codestral Embed can output embeddings with different dimensions and precisions; for instance, with a dimension of 256 and int8 precision, it still performs better than any model from competitors. The dimensions of the embeddings are ordered by relevance, allowing users to choose the first n dimensions for a smooth trade-off between quality and cost. It excels in retrieval use cases on real-world code data, particularly in benchmarks like SWE-Bench, which is based on real-world GitHub issues and corresponding fixes, and Text2Code (GitHub), relevant for providing context for code completion or editing.
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