ToolPicker
Voyage AI Rerank

Voyage AI Rerank

36/100

rerank-2.5 instruction-following reranker for RAG.

docs.voyageai.com

// scorecard · 36/100

verified 1mo ago
methodology →
Agent-readiness14/35
Agent registration (api_key)6/9
Public API5/5
OpenAPI spec0/9
MCP server0/9
llms.txt3/3
Reliability & performance0/15
Actively maintained
Production-ready0/4
Updated recently
Pricing8/13
Itemized public pricing6/6
Free tier / trial0/4
Free-tier generosity2/3
Docs & DX2/12
Docs quality
Public API2/2
Quickstart / examples0/2
Security & compliance8/12
SOC 26/6
ISO 270010/2
GDPR0/2
Security / trust page2/2
Openness4/10
Open source0/6
Open / un-gated API4/4
Company maturity0/3
Company size
Years operating

// rankings · cost per standard workload

#3 in Rerankers$0.5/ 1k rerank searches

rerank-2.5 $0.05/1M tokens x10M = $0.50/mo (per-token)

docs.voyageai.com/docs/pricing

// overview

Voyage AI provides embedding models that convert documents, images, audio, video or tabular data into semantic vectors for search and RAG, plus rerankers that score query-document relevance to refine results from embeddings or lexical search. It exposes API endpoints returning embeddings or relevance scores that integrate with vector stores and LLMs. Models are stated to be state-of-the-art for retrieval accuracy.

Best for: domain-specific or company-specific chatbots and other AI applications

// pricing

voyage-4-large$0.00012 per thousand tokens
  • 200M free tokens
voyage-4$0.00006 per thousand tokens
  • 200M free tokens
rerank-2.5$0.00005 per thousand tokens
  • 200M free tokens

// security & compliance

SOC 2 ISO 27001 GDPR HIPAA

// features

  • Text Embeddings
  • Multimodal Embeddings
  • Rerankers
  • Contextualized Chunk Embeddings
  • Batch Inference
  • Flexible Dimensions and Quantization

sources