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voyageai

VoyageAI by MongoDB: voyage-code-4

Source description (English)

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...

View source on OpenRouter

Overview

Model specifications

Context: 32,000 tokens
Maximum output: 28,800 tokens
Architecture: text->embeddings
Tokenizer: Other
Knowledge cutoff: Not provided
Moderated: No

OPENROUTER

Complete pricing

Synchronized OpenRouter rates. Token prices are shown per one million tokens.

Input: $0.12

API

Quick start

Set OPENROUTER_API_KEY locally. Python requires requests; JavaScript runs in Node.js. Keep the key on the server.

API documentation

curl --fail-with-body https://openrouter.ai/api/v1/embeddings \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"voyageai/voyage-code-4","input":"Your text here"}'

Capabilities

Input → Output

Input

text

Output

embeddings

API

Supported API parameters

Available providers

1 Provider

Checked: September 7, 2026

Live providers on OpenRouter

Provider availability, latency, throughput and routing can change continuously. Open the source page for current operational data.

VoyageAI by MongoDB

Not provided

Context: 32K
Maximum output: 29K
Input: $0.12
Output: Free
Cache read: Not provided
Cache write: Not provided

voyageai

4 models

Released Jul 27, 2026

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...

Context: 32K
Input: text
Output: rerank

Input: $0.02 per million input tokens

View model details →

Released Jul 27, 2026

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%...

Context: 32K
Input: text
Output: rerank

Input: $0.05 per million input tokens

View model details →

Released Jul 27, 2026

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...

Context: 32K
Input: text · image
Output: embeddings

Input: $0.12per 1M tokens

View model details →

Released Jul 27, 2026

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,...

Context: 32K
Input: text
Output: embeddings

Input: $0.02per 1M tokens

View model details →