GPT-4V (Vision) Customer Reviews in April 2025

What is GPT-4V (Vision)?

The recent development of GPT-4 with vision (GPT-4V) empowers users to instruct GPT-4 to analyze image inputs they submit, representing a pivotal advancement in enhancing its capabilities. Experts in the domain regard the fusion of different modalities, such as images, with large language models (LLMs) as an essential facet for future advancements in artificial intelligence. By incorporating these multimodal features, LLMs have the potential to improve the efficiency of conventional language systems, leading to the creation of novel interfaces and user experiences while addressing a wider spectrum of tasks. This system card is dedicated to evaluating the safety measures associated with GPT-4V, building on the existing safety protocols established for its predecessor, GPT-4. In this document, we explore in greater detail the assessments, preparations, and methodologies designed to ensure safety in relation to image inputs, thereby underscoring our dedication to the responsible advancement of AI technology. Such initiatives not only protect users but also facilitate the ethical implementation of AI breakthroughs, ensuring that innovations align with societal values and ethical standards. Moreover, the pursuit of safety in AI systems is vital for fostering trust and reliability in their applications.

Integrations

All GPT-4V (Vision) Integrations

Similar Software to GPT-4V (Vision)

LM-Kit.NET

(3 Ratings)

LM-Kit.NET serves as a comprehensive toolkit tailored for the seamless incorporation of generative AI into .NET applications, fully compatible with Windows, Linux, and macOS systems. This versatile platform empowers your C# and VB.NET projects, facilitating the development and management of dynamic AI agents with ease. Utilize efficient Small Language Models for on-device inference, which effectively lowers computational demands, minimizes latency, and enhances security by processing information locally. Discover the advantages of Retrieval-Augmented Generation (RAG) that improve both accuracy and relevance, while sophisticated AI agents streamline complex tasks and expedite the development process. With native SDKs that guarantee smooth integration and optimal performance across various platforms, LM-Kit.NET also offers extensive support for custom AI agent creation and multi-agent orchestration. This toolkit simplifies the stages of prototyping, deployment, and scaling, enabling you to create intelligent, rapid, and secure solutions that are relied upon by industry professionals globally, fostering innovation and efficiency in every project.

Learn more

Vertex AI

(673 Ratings)

Completely managed machine learning tools facilitate the rapid construction, deployment, and scaling of ML models tailored for various applications. Vertex AI Workbench seamlessly integrates with BigQuery Dataproc and Spark, enabling users to create and execute ML models directly within BigQuery using standard SQL queries or spreadsheets; alternatively, datasets can be exported from BigQuery to Vertex AI Workbench for model execution. Additionally, Vertex Data Labeling offers a solution for generating precise labels that enhance data collection accuracy. Furthermore, the Vertex AI Agent Builder allows developers to craft and launch sophisticated generative AI applications suitable for enterprise needs, supporting both no-code and code-based development. This versatility enables users to build AI agents by using natural language prompts or by connecting to frameworks like LangChain and LlamaIndex, thereby broadening the scope of AI application development.

Learn more

Qwen2-VL

Qwen2-VL stands as the latest and most sophisticated version of vision-language models in the Qwen lineup, enhancing the groundwork laid by Qwen-VL. This upgraded model demonstrates exceptional abilities, including: Delivering top-tier performance in understanding images of various resolutions and aspect ratios, with Qwen2-VL particularly shining in visual comprehension challenges such as MathVista, DocVQA, RealWorldQA, and MTVQA, among others. Handling videos longer than 20 minutes, which allows for high-quality video question answering, engaging conversations, and innovative content generation. Operating as an intelligent agent that can control devices such as smartphones and robots, Qwen2-VL employs its advanced reasoning abilities and decision-making capabilities to execute automated tasks triggered by visual elements and written instructions. Offering multilingual capabilities to serve a worldwide audience, Qwen2-VL is now adept at interpreting text in several languages present in images, broadening its usability and accessibility for users from diverse linguistic backgrounds. Furthermore, this extensive functionality positions Qwen2-VL as an adaptable resource for a wide array of applications across various sectors.

Learn more

LLaVA

LLaVA, which stands for Large Language-and-Vision Assistant, is an innovative multimodal model that integrates a vision encoder with the Vicuna language model, facilitating a deeper comprehension of visual and textual data. Through its end-to-end training approach, LLaVA demonstrates impressive conversational skills akin to other advanced multimodal models like GPT-4. Notably, LLaVA-1.5 has achieved state-of-the-art outcomes across 11 benchmarks by utilizing publicly available data and completing its training in approximately one day on a single 8-A100 node, surpassing methods reliant on extensive datasets. The development of this model included creating a multimodal instruction-following dataset, generated using a language-focused variant of GPT-4. This dataset encompasses 158,000 unique language-image instruction-following instances, which include dialogues, detailed descriptions, and complex reasoning tasks. Such a rich dataset has been instrumental in enabling LLaVA to efficiently tackle a wide array of vision and language-related tasks. Ultimately, LLaVA not only improves interactions between visual and textual elements but also establishes a new standard for multimodal artificial intelligence applications. Its innovative architecture paves the way for future advancements in the integration of different modalities.

Learn more

Screenshots and Video

Company Facts

Company Name:

OpenAI

Date Founded:

2015

Company Location:

United States

Company Website:

openai.com/research/gpt-4v-system-card

Product Details

Deployment

SaaS

Training Options

Documentation Hub

Support

Web-Based Support

Product Details

Target Company Sizes

Individual

1-10

11-50

51-200

201-500

501-1000

1001-5000

5001-10000

10001+

Target Organization Types

Mid Size Business

Small Business

Enterprise

Freelance

Nonprofit

Government

Startup

Supported Languages

Albanian

Arabic

Armenian

Basque

Bengali

Bulgarian

Catalan

Chinese (Mandarin)

Chinese (Simplified)

Croatian

Czech

Danish

Dutch

English

Estonian

Finnish

French

View All

More GPT-4V (Vision) Categories

Multimodal Models

Foundation Models