RankLLM

RankLLM

Castorini
voyage-4-large

voyage-4-large

Voyage AI
+
+

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About

RankLLM is a Python toolkit for reproducible information retrieval research using rerankers, with a focus on listwise reranking. It offers a suite of rerankers, pointwise models like MonoT5, pairwise models like DuoT5, and listwise models compatible with vLLM, SGLang, or TensorRT-LLM. Additionally, it supports RankGPT and RankGemini variants, which are proprietary listwise rerankers. It includes modules for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. RankLLM integrates with Pyserini for retrieval and provides integrated evaluation for multi-stage pipelines. It also 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.

About

The Voyage 4 model family from Voyage AI is a new generation of text embedding models designed to produce high-quality semantic vectors with an industry-first shared embedding space that lets different models in the series generate compatible embeddings so developers can mix and match models for document and query embedding to optimize accuracy, latency, and cost trade-offs. It includes voyage-4-large (a flagship model using a mixture-of-experts architecture delivering state-of-the-art retrieval accuracy at about 40% lower serving cost than comparable dense models), voyage-4 (balancing quality and efficiency), voyage-4-lite (high-quality embeddings with fewer parameters and lower compute cost), and the open-weight voyage-4-nano (ideal for local development and prototyping with an Apache 2.0 license). All four models in the series operate in a single shared embedding space, so embeddings generated by different variants are interchangeable, enabling asymmetric retrieval strategies.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Academic researchers and developers seeking a solution offering tools for implementing and evaluating listwise reranking with large language models

Audience

AI developers and engineers building retrieval-based AI systems, semantic search, and context-aware agents who need high-accuracy, flexible, and cost-optimized text embedding models

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Castorini
Canada
github.com/castorini/rank_llm/

Company Information

Voyage AI
Founded: 2023
United States
blog.voyageai.com/2026/01/15/voyage-4/

Alternatives

RankGPT

RankGPT

Weiwei Sun

Alternatives

Voyage AI

Voyage AI

MongoDB
ColBERT

ColBERT

Future Data Systems
Codestral Embed

Codestral Embed

Mistral AI

Categories

Categories

Integrations

Gemini
OpenAI
Cohere Embed
Gemini Enterprise
Hugging Face
Llama
Mistral AI
MongoDB Atlas
NVIDIA TensorRT
Python
Qwen
RankGPT
Voyage AI

Integrations

Gemini
OpenAI
Cohere Embed
Gemini Enterprise
Hugging Face
Llama
Mistral AI
MongoDB Atlas
NVIDIA TensorRT
Python
Qwen
RankGPT
Voyage AI
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