Compare the Top Reranking Models that integrate with Snowflake as of November 2025

This a list of Reranking Models that integrate with Snowflake. Use the filters on the left to add additional filters for products that have integrations with Snowflake. View the products that work with Snowflake in the table below.

What are Reranking Models for Snowflake?

Reranking models are AI models in information retrieval systems that refine the order of retrieved documents to better match user queries. Typically employed in two-stage retrieval pipelines, these models first generate a broad set of candidate documents and then reorder them based on relevance. They utilize sophisticated techniques, such as deep learning models like BERT, T5, and their multilingual variants, to capture complex semantic relationships between queries and documents. The primary advantage of reranking models lies in their ability to improve the precision of search results, ensuring that the most pertinent documents are presented to the user. However, this enhanced accuracy often comes at the cost of increased computational resources and potential latency. Despite these challenges, rerankers are integral to applications requiring high-quality information retrieval, such as question answering, semantic search, and recommendation systems. Compare and read user reviews of the best Reranking Models for Snowflake currently available using the table below. This list is updated regularly.

  • 1
    Pinecone Rerank v0
    Pinecone Rerank V0 is a cross-encoder model optimized for precision in reranking tasks, enhancing enterprise search and retrieval-augmented generation (RAG) systems. It processes queries and documents together to capture fine-grained relevance, assigning a relevance score from 0 to 1 for each query-document pair. The model's maximum context length is set to 512 tokens to preserve ranking quality. Evaluations on the BEIR benchmark demonstrated that Pinecone Rerank V0 achieved the highest average NDCG@10, outperforming other models on 6 out of 12 datasets. For instance, it showed up to a 60% boost on the Fever dataset compared to Google Semantic Ranker and over 40% on the Climate-Fever dataset relative to cohere-v3-multilingual or voyageai-rerank-2. The model is accessible through Pinecone Inference and is available to all users in public preview.
    Starting Price: $25 per month
  • 2
    Voyage AI

    Voyage AI

    Voyage AI

    Voyage AI delivers state-of-the-art embedding and reranking models that supercharge intelligent retrieval for enterprises, driving forward retrieval-augmented generation and reliable LLM applications. Available through all major clouds and data platforms. SaaS and customer tenant deployment (in-VPC). Our solutions are designed to optimize the way businesses access and utilize information, making retrieval faster, more accurate, and scalable. Built by academic experts from Stanford, MIT, and UC Berkeley, alongside industry professionals from Google, Meta, Uber, and other leading companies, our team develops transformative AI solutions tailored to enterprise needs. We are committed to pushing the boundaries of AI innovation and delivering impactful technologies for businesses. Contact us for custom or on-premise deployments as well as model licensing. Easy to get started, pay as you go, with consumption-based pricing.
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