Audience
AI researchers needing a tool to leverage LLMs for advanced document reranking in information retrieval systems
About RankGPT
RankGPT is a Python toolkit designed to explore the use of generative Large Language Models (LLMs) like ChatGPT and GPT-4 for relevance ranking in Information Retrieval (IR). It introduces methods such as instructional permutation generation and a sliding window strategy to enable LLMs to effectively rerank documents. It supports various LLMs, including GPT-3.5, GPT-4, Claude, Cohere, and Llama2 via LiteLLM. RankGPT provides modules for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. It includes a module for detailed analysis of input prompts and LLM responses, addressing reliability concerns with LLM APIs and non-deterministic behavior in Mixture-of-Experts (MoE) models. The toolkit supports various backends, including SGLang and TensorRT-LLM, and is compatible with a wide range of LLMs. RankGPT's Model Zoo includes models like LiT5 and MonoT5, hosted on Hugging Face.
Other Popular Alternatives & Related Software
Diploria AI
Diploria AI is an AI visibility platform that tracks, analyzes and optimizes how brands are mentioned and recommended by ChatGPT, Claude, Gemini, Perplexity, Grok, Copilot and other AI engines, benchmarking you against competitors to win more AI recommendations.
Track - Runs prompts through live APIs on 12 major AI engines incl. Google AI Mode/Overviews, storing every real response, on a schedule you choose.
Analyze - A 0-100 Visibility Score benchmarks how often your brand appears in AI answers, weighted across prompts, engines and locations. Track sentiment, benchmark competitors, simulate markets.
Optimize - The AI Readiness Scan audits any URL out of 100 across five pillars, delivering a prioritized checklist.
Connect Google Analytics 4 to see real AI referral traffic from ChatGPT, Perplexity, Claude, Gemini and other sources.
Built for brands and agencies: manage client brands, export reports, invite your team with role-based access. Free plan available/no card req.
Learn more
Muse Spark Open
Muse Spark Open is an open-weight, natively multimodal language model for developers and organizations building AI applications, coding systems, and agentic workflows. The released model has 816 billion total parameters, 42 billion active parameters, and a 1-million-token context window. Teams can download the model weights, run inference through supported engines such as vLLM, SGLang, TensorRT-LLM, Hugging Face Transformers, Apple MLX, llama.cpp, or Unsloth, and customize the model using PyTorch. It supports long-context reasoning, software engineering, coding, tool use, and multimodal inputs. Deployment options include cloud inference through listed API providers or self-hosting on compatible GPU systems; Meta documents a desktop setup using two Apple M5 Ultra Mac Studio computers. The model is released under the Muse Model License with limited commercial terms.
Learn more
Nemotron 3.5 Super VL
NVIDIA Nemotron 3.5 Super VL is an open, customizable multimodal AI model designed for complex reasoning, autonomous agents, and enterprise workflows. The model uses a 120-billion-parameter mixture-of-experts architecture that activates approximately 12 billion parameters per token to balance computational efficiency with model capabilities. It combines text, image, document, and video understanding with instruction following, coding, and external tool use. Its multimodal capabilities support document analysis, chart interpretation, optical character recognition, video understanding, and automated information extraction. Developers can customize the model through supervised fine-tuning, low-rank adaptation, and reinforcement learning using NVIDIA NeMo. Nemotron 3.5 Super VL supports deployment in local, cloud, and data center environments for applications such as software engineering, financial document processing, cybersecurity analysis, and enterprise automation.
Learn more
Amazon Personalize
Amazon Personalize enables developers to build applications with the same machine learning (ML) technology used by Amazon.com for real-time personalized recommendations – no ML expertise required. Amazon Personalize makes it easy for developers to build applications capable of delivering a wide array of personalization experiences, including specific product recommendations, personalized product re-ranking, and customized direct marketing. Amazon Personalize is a fully managed machine learning service that goes beyond rigid static rule based recommendation systems and trains, tunes, and deploys custom ML models to deliver highly customized recommendations to customers across industries such as retail and media and entertainment. Amazon Personalize provisions the necessary infrastructure and manages the entire ML pipeline, including processing the data, identifying features, using the best algorithms, and training, optimizing, and hosting the models.
Learn more
Pricing
Starting Price:
Free
Free Version:
Free Version available.
Company Information
Weiwei Sun
United States
github.com/sunnweiwei/RankGPT
Videos and Screen Captures
Other Useful Business Software
Build Agents and Models on One Platform
Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
Product Details
Platforms Supported
Cloud
Training
Documentation
Support
Online
