Models Model details

VoyageAI

VoyageAI by MongoDB: rerank-3

voyageai/rerank-3

rerank-3 is a reranker optimized for quality and a drop-in upgrade to rerank-2.5, improving on it by 0.80% NDCG@10 on average across domain evaluations and by 3.35% on long-document evaluations, with code retrieval gains of 2.01% atop voyage-3-large and 1.96% atop voyage-4-large. Across 93 retrieval datasets it outperforms Cohere Rerank v4.0 Pro by 2.14% and Qwen3-Reranker-8B by 3.31%. The model supports a combined context length of 32K tokens per query-document pair, including up to 8K tokens for the query, enabling more accurate retrieval over longer documents. Additionally, rerank-3 supports instruction following, allowing users to guide relevance scoring through natural language prompts. Learn more about rerank-3 here: blog.voyageai.com/2026/09/30/rerank-3

Input
$0

/ 1M tokens · Token reference

Output
$0

/ 1M tokens · Token reference

Context window
32K

tokens

Rerank output · Token reference fields do not establish an output-unit price.

Limits

Context

32,000

tokens

Max output

28,800

90% of the context window

Model facts

Author

VoyageAI

Tokenizer

Other

Modality

Text -> Rerank

Created

Sep 30, 2026

Publication status

Hugging Face: not mappedLicense: not publishedParameter count: not published

Modalities

Input · TextOutput · Rerank