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Description

NVIDIA Nemotron 3.5 Super VL is a multimodal foundation model developed for AI agents that require reasoning, visual understanding, coding, and multistep task execution. Its 120-billion-parameter mixture-of-experts architecture activates approximately 12 billion parameters per token, enabling efficient inference while maintaining substantial model capacity. The model processes text, images, documents, and video within a unified system that combines multimodal interpretation with instruction following and tool use. Its document intelligence capabilities include extracting information from tables, analyzing charts, interpreting page layouts, and processing multipage documents. Video understanding features support visual information retrieval, content review, incident analysis, and reasoning across recorded sequences. The model also supports software engineering tasks such as code analysis, error identification, debugging, testing, and recommending fixes. Developers can customize Nemotron 3.5 Super VL using NVIDIA NeMo for supervised fine-tuning, low-rank adaptation, and reinforcement learning with domain-specific data. Its inference optimizations include speculative decoding, context reuse, multi-token prediction, and NVFP4 quantization to improve throughput and reduce computational requirements. The model is available with open weights and supports deployment across compatible local hardware, enterprise data centers, and cloud infrastructure.

Description

RankGPT is a Python toolkit specifically crafted to delve into the application of generative Large Language Models (LLMs), such as ChatGPT and GPT-4, for the purpose of relevance ranking within Information Retrieval (IR). It presents innovative techniques, including instructional permutation generation and a sliding window strategy, which help LLMs to efficiently rerank documents. Supporting a diverse array of LLMs—including GPT-3.5, GPT-4, Claude, Cohere, and Llama2 through LiteLLM—RankGPT offers comprehensive modules for retrieval, reranking, evaluation, and response analysis, thereby streamlining end-to-end processes. Additionally, the toolkit features a module dedicated to the in-depth analysis of input prompts and LLM outputs, effectively tackling reliability issues associated with LLM APIs and the non-deterministic nature of Mixture-of-Experts (MoE) models. Furthermore, it is designed to work with multiple backends, such as SGLang and TensorRT-LLM, making it compatible with a broad spectrum of LLMs. Among its resources, RankGPT's Model Zoo showcases various models, including LiT5 and MonoT5, which are conveniently hosted on Hugging Face, allowing users to easily access and implement them in their projects. Overall, RankGPT serves as a versatile and powerful toolkit for researchers and developers aiming to enhance the effectiveness of information retrieval systems through advanced LLM techniques.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

ChatGPT No 
Claude No 
Claude Duet No 
Claude for Legal No 
Cohere No 
GPT-3.5 No 
GPT-4 No 
Hugging Face No 
LiteLLM No 
Llama 2 No 
NVIDIA NIM Yes 
NVIDIA TensorRT No 
OpenRouter Yes 
Python No 
RankLLM No 
vLLM Yes 

Integrations

ChatGPT Yes 
Claude Yes 
Claude Duet Yes 
Claude for Legal Yes 
Cohere Yes 
GPT-3.5 Yes 
GPT-4 Yes 
Hugging Face Yes 
LiteLLM Yes 
Llama 2 Yes 
NVIDIA NIM No 
NVIDIA TensorRT Yes 
OpenRouter No 
Python Yes 
RankLLM Yes 
vLLM No 

Pricing Details

$0
The model is available at no charge under the OpenMDW-1.1 license. Hosted inference through third-party providers may have separate charges.
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

nvidia.com

Vendor Details

Company Name

Weiwei Sun

Country

United States

Website

github.com/sunnweiwei/RankGPT

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