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VoyageAI by MongoDB: rerank-2.5-lite

Descripción de la fuente (inglés)

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...

Ver fuente en OpenRouter
Resumen

Especificaciones del modelo

Contexto
32.000 tokens
Salida máxima
28.800 tokens
Arquitectura
text->rerank
Tokenizador
Other
Corte de conocimiento
No indicado
Moderado
No
OPENROUTER

Precios completos

Tarifas sincronizadas desde OpenRouter, por millón de tokens.

Entrada
$0.02
por millón de tokens de entrada
API

Inicio rápido

Configura OPENROUTER_API_KEY localmente. Python requiere requests; JavaScript se ejecuta en Node.js. Mantén la clave en el servidor.

Documentación de la 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-2.5-lite","query":"What is the capital of France?","documents":["Paris is the capital of France.","Berlin is the capital of Germany."],"top_n":1}'
Capacidades y modalidades

Entrada → Salida

Entrada
text
Salida
rerank
API

Parámetros API compatibles

Proveedores disponibles

1 Proveedor

Verificado: 7 de septiembre de 2026

Proveedores en vivo en OpenRouter

Disponibilidad, latencia, rendimiento y enrutamiento cambian continuamente. Consulta la fuente para datos actuales.

OpenRouter

VoyageAI by MongoDB

No indicado
Contexto
32K
Salida máxima
29K
voyageai

4 modelos

Todos los modelos
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 2048, 1024, 512, and 256...

Contexto
32K
Entrada
text
Salida
embeddings
Entrada: $0.12por millón de tokens
Ver detalles del modelo →
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%...

Contexto
32K
Entrada
text
Salida
rerank
Entrada: $0.05 por millón de tokens de entrada
Ver detalles del modelo →
voyageai logovoyageai

VoyageAI by MongoDB: voyage-multimodal-3.5

voyage-multimodal-3.5 is a state-of-the-art multimodal embedding model capable of vectorizing not only text, images, and video individually, but also content that interleaves all three modalities. It delivers excellent performance for...

Contexto
32K
Entrada
text · image
Salida
embeddings
Entrada: $0.12por millón de tokens
Ver detalles del modelo →
voyageai logovoyageai

VoyageAI by MongoDB: voyage-4-lite

voyage-4-lite is a lightweight, general-purpose embedding model optimized for low latency and cost. Enabled by Matryoshka learning and quantization-aware training, voyage-4-lite supports embeddings in 2048, 1024, 512, and 256 dimensions,...

Contexto
32K
Entrada
text
Salida
embeddings
Entrada: $0.02por millón de tokens
Ver detalles del modelo →