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VoyageAI by MongoDB: rerank-3

Descrizione della fonte (inglese)

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,...

Vedi la fonte su OpenRouter
Panoramica

Specifiche del modello

Contesto
32.000 tokens
Output massimo
28.800 tokens
Architettura
text->rerank
Tokenizer
Other
Limite di conoscenza
Non indicato
Moderato
No
OPENROUTER

Prezzi completi

Tariffe sincronizzate da OpenRouter, per milione di token.

Input
$0.05
per milione di token di input
API

Avvio rapido

Imposta OPENROUTER_API_KEY localmente. Python richiede requests; JavaScript viene eseguito in Node.js. Conserva la chiave sul server.

Documentazione API

curl --fail-with-body https://openrouter.ai/api/v1/rerank \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"voyageai/rerank-3","query":"What is the capital of France?","documents":["Paris is the capital of France.","Berlin is the capital of Germany."],"top_n":1}'
Capacità e modalità

Input → Output

Input
text
Output
rerank
API

Parametri API supportati

Provider disponibili

1 Provider

Verificato: 2 ottobre 2026

Provider live su OpenRouter

Disponibilità, latenza, throughput e routing cambiano continuamente. Consulta la fonte per i dati correnti.

OpenRouter

VoyageAI by MongoDB

Non indicato
Contesto
32K
Output massimo
29K
voyageai

4 modelli

Tutti i modelli
voyageai logovoyageai

VoyageAI by MongoDB: rerank-3-lite

rerank-3-lite is a reranker optimized for both latency and quality and a drop-in upgrade to rerank-2.5-lite, improving on it by 0.94% NDCG@10 on average across domain evaluations and by 1.86%...

Contesto
32K
Input
text
Output
rerank
Input: $0.02 per milione di token di input
Vedi i dettagli del modello →
voyageai logovoyageai

VoyageAI by MongoDB: voyage-code-4

voyage-code-4 is a code embedding model from Voyage AI, a MongoDB company. It is designed for coding agents and code retrieval, with Matryoshka embeddings at 2048t voyage-code-4 here: mongodb.com/products/platform/ai-search-and-retrieval/models

Contesto
32K
Input
text
Output
embeddings
Input: $0.12per milione di token
Vedi i dettagli del modello →
voyageai logovoyageai

VoyageAI by MongoDB: rerank-2.5-lite

rerank-2.5-lite is a reranker optimized for both latency and quality, delivering a 7.16% improvement in retrieval accuracy over Cohere Rerank v3.5 across 93 datasets. It also outperformed Cohere Rerank v3.5...

Contesto
32K
Input
text
Output
rerank
Input: $0.02 per milione di token di input
Vedi i dettagli del modello →
voyageai logovoyageai

VoyageAI by MongoDB: rerank-2.5

rerank-2.5 is a cutting-edge reranker optimized for quality, delivering a 7.94% improvement in retrieval accuracy over Cohere Rerank v3.5 across 93 datasets. It also outperformed Cohere Rerank v3.5 by 12.70%...

Contesto
32K
Input
text
Output
rerank
Input: $0.05 per milione di token di input
Vedi i dettagli del modello →