Rerank 3

Enterprise-grade search and retrieval enhanced foundational model

EditorRecommendationBusinessEnterprise SearchRetrieval-Augmented Generation

Visit

Rerank 3 is a new foundational model optimized for enterprise search and retrieval-augmented generation (RAG) systems. It supports multilingual and multi-structured data search, provides high-precision semantic ranking, significantly improves response accuracy and latency, and greatly reduces the overall cost of ownership. Rerank 3 can be seamlessly integrated into any database or search engine and supports seamless integration with existing applications' native search functionality.

Product Finder

Product Submit

AI Models Finder

MCP Servers

MCP Client

MCP Inspector

Case Tutorials

Latest AI News

AI Daily Brief

Rerank 3

Rerank 3 Visit Over Time

Rerank 3 Visit Trend

Rerank 3 Visit Geography

Rerank 3 Traffic Sources

Rerank 3 Alternatives

Rerank 3 — Enterprise-grade search and retrieval enhanced foundational model

LightRAG — A simple and fast retrieval-augmented generation model

VisRAG — A retrieval-augmented generation model based on visual language modeling.

LongRAG — Enhanced Retrieval-Augmented Generation Model for Long-Text Question Answering

M2RAG — A benchmark codebase for retrieval-augmented generation in multimodal contexts.

Nemotron-Mini-4B-Instruct — A compact language model designed for role-playing, retrieval-augmented generation, and function invocation.

ArguflowChat — A retrieval-augmented LLM chatbot that allows you to chat with Garry Tan.

SkyPilot RAG — SkyPilot RAG is a retrieval-augmented generation system based on SkyPilot, used for processing large-scale legal document search and analysis.

MedRAG — A retrieval-augmented question-answering model for the medical field

bRAG-langchain — An open-source project for building Retrieval-Augmented Generation (RAG) applications.

KET-RAG — KET-RAG is a retrieval-augmented generation framework that incorporates knowledge graphs for efficient document indexing and answer generation.

VideoRAG — VideoRAG is a retrieval-augmented generation framework designed for processing videos with extremely long context.

MiniRAG — A simple retrieval-augmented generation framework that enables small models to achieve good RAG performance through heterogeneous graph indexing and lightweight topological enhanced retrieval.

Command-R — Command-R is a new LLM designed for large production workloads, optimized for RAG (Retrieval Augmented Generation) and tool use to achieve enterprise-grade production-scale AI.

OpenScholar — A retrieval-augmented language model for synthesizing scientific literature.

RAG_Techniques — A revolutionary collection of Retrieval-Augmented Generation system technologies.

c4ai-command-r7b-12-2024 — A multilingual text generation model with 7 billion parameters.

FlashRAG — Efficient Toolkit for Retrieval-Augmented Generation Research

C4AI CommandR 08-2024 — A high-performance generation model with 3.5 billion parameters

RAG Search API — An intelligent search API providing efficient information retrieval.

NVIDIA Project GR00T — A general-purpose foundational model for learning in humanoid robots.

Ragie — Developer-friendly Retrieval-Augmented Generation as a Service.

ViDoRAG — ViDoRAG is a dynamic iterative reasoning agent framework that combines visual document retrieval and enhanced generation.

RAGFlow — An open-source Retrieval-Augmented Generation (RAG) engine based on deep document understanding

C4AI Command R+ 08-2024 — A multilingual advanced dialogue generation model with 104 billion parameters.

Mirageml — Enterprise Asset Search Engine

RAGLAB — A modular, research-oriented unified framework for retrieval-augmented generation

Gemini-Search — An AI search engine styled after Perplexity, based on the Gemini 2.0 Flash model.

ASAL — A foundational model for automated searching in artificial life.

RAGFoundry — A framework for enhancing retrieval-augmented generation tasks with LLMs.