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Voyage Code 3

The code-retrieval embedding behind Cursor and Continue — 32K context, Matryoshka dims.

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About

voyage-code-3, released December 4, 2024, is Voyage AI's code-tuned embedding model — and one of the most widely deployed retrieval models in the AI coding ecosystem, serving as the retrieval engine behind assistants like Cursor, Continue, and Cody. It offers a 32K-token context window with Matryoshka-configurable output dimensions (256/512/1024/2048) and multiple precisions.

Voyage reported it beating OpenAI's text-embedding-3-large by nearly 14% on average across code retrieval datasets, with particular strength on CodeSearchNet. The flexible dimensions let teams store embeddings at a third the size of competitors at comparable accuracy — a practical win for large codebases.

Honest caveats: it is API-only (no open weights), benchmark claims are Voyage's, and the 2026 voyage-code-4 release has since superseded it for agent-heavy workloads. Pricing and rate limits are tiered by account. For code RAG where retrieval quality is the bottleneck, it remains a proven default.

Specs

Context window

Pricing

Free quota

API access

Weights

Closed — API only

Released

December 4, 2024

Benchmarks

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

embeddingscode-searchrag

Trust score — 8/10

/10 trustVerified

Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 61; Trending score 78/100 from researcher assessment.

Sources