Compare the Top Large Language Models that integrate with Singulr as of May 2026

This a list of Large Language Models that integrate with Singulr. Use the filters on the left to add additional filters for products that have integrations with Singulr. View the products that work with Singulr in the table below.

What are Large Language Models for Singulr?

Large language models are artificial neural networks used to process and understand natural language. Commonly trained on large datasets, they can be used for a variety of tasks such as text generation, text classification, question answering, and machine translation. Over time, these models have continued to improve, allowing for better accuracy and greater performance on a variety of tasks. Compare and read user reviews of the best Large Language Models for Singulr currently available using the table below. This list is updated regularly.

  • 1
    ChatGPT

    ChatGPT

    OpenAI

    ChatGPT is an AI-powered assistant designed to help users get answers, generate ideas, and complete tasks more efficiently. It supports a wide range of activities, including writing, brainstorming, coding, and research. Users can interact with ChatGPT through text or voice, making it flexible for different use cases. The platform can summarize information, analyze data, and provide insights to improve productivity. It also assists with creative tasks such as content creation, planning, and problem-solving. ChatGPT includes workspace agents that can automate workflows, handle repetitive tasks, and operate across tools. These agents can run tasks independently, such as generating reports or managing processes on a schedule. Overall, ChatGPT serves as a versatile tool for both personal and professional use.
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    Starting Price: Free
  • 2
    Claude

    Claude

    Anthropic

    Claude is a next-generation AI assistant developed by Anthropic to help individuals and teams solve complex problems with safety, accuracy, and reliability at its core. It is designed to support a wide range of tasks, including writing, editing, coding, data analysis, and research. Claude allows users to create and iterate on documents, websites, graphics, and code directly within chat using collaborative tools like Artifacts. The platform supports file uploads, image analysis, and data visualization to enhance productivity and understanding. Claude is available across web, iOS, and Android, making it accessible wherever work happens. With built-in web search and extended reasoning capabilities, Claude helps users find information and think through challenging problems more effectively. Anthropic emphasizes security, privacy, and responsible AI development to ensure Claude can be trusted in professional and personal workflows.
    Starting Price: Free
  • 3
    Gemini

    Gemini

    Google

    Gemini is Google’s advanced AI assistant designed to help users think, create, learn, and complete tasks with a new level of intelligence. Powered by Google’s most capable models, including Gemini 3, it enables users to ask complex questions, generate content, analyze information, and explore ideas through natural conversation. Gemini can create images, videos, summaries, study plans, and first drafts while also providing feedback on uploaded files and written work. The platform is grounded in Google Search, allowing it to deliver accurate, up-to-date information and support deep follow-up questions. Gemini connects seamlessly with Google apps like Gmail, Docs, Calendar, Maps, YouTube, and Photos to help users complete tasks without switching tools. Features such as Gemini Live, Deep Research, and Gems enhance brainstorming, research, and personalized workflows. Available through flexible free and paid plans, Gemini supports everyday users, students, and professionals across devices.
    Starting Price: Free
  • 4
    Llama

    Llama

    Meta

    Llama (Large Language Model Meta AI) is a state-of-the-art foundational large language model designed to help researchers advance their work in this subfield of AI. Smaller, more performant models such as Llama enable others in the research community who don’t have access to large amounts of infrastructure to study these models, further democratizing access in this important, fast-changing field. Training smaller foundation models like Llama is desirable in the large language model space because it requires far less computing power and resources to test new approaches, validate others’ work, and explore new use cases. Foundation models train on a large set of unlabeled data, which makes them ideal for fine-tuning for a variety of tasks. We are making Llama available at several sizes (7B, 13B, 33B, and 65B parameters) and also sharing a Llama model card that details how we built the model in keeping with our approach to Responsible AI practices.
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