voyage code-4 AI Foundry

As described on Microsoft Marketplace.

Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality. voyage-code-4 is a next-generation code embedding model purpose-built for coding agents. It outperforms Cohere Embed v4 and Gemini Embedding 2 by an average of 28.25% and 31.03% on agentic code retrieval, a new benchmark built from issue-fixing pull requests, and by 19.21% and 16.01% across the 28 code retrieval datasets used to evaluate voyage-code-3. It surpasses voyage-code-3 itself by 27.54% and 13.98% on those two suites, respectively. Enabled by Matryoshka learning and quantization-aware training, voyage-code-4 supports embeddings in 2048, 1024, 512, and 256 dimensions, with multiple quantization options, and is priced at $0.12 per 1M tokens. Learn more about voyage-code-4 here: https://blog.voyageai.com/2026/08/13/voyage-code-4