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

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

What are Large Language Models for PromptX?

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 PromptX currently available using the table below. This list is updated regularly.

  • 1
    Grok

    Grok

    xAI

    Grok is an advanced AI assistant developed by xAI, designed to provide real-time insights, intelligent responses, and conversational support. It is deeply integrated with the X (formerly Twitter) platform, allowing users to access up-to-date information and trending discussions. Grok is built to answer complex questions with a mix of reasoning, humor, and personality. It can assist with tasks such as research, content creation, and general problem-solving. The platform leverages large language models to deliver accurate and context-aware responses. Grok stands out for its ability to access live data, making it highly relevant for current events. Overall, it offers a dynamic and engaging AI experience for everyday users.
    Starting Price: Free
  • 2
    Qwen

    Qwen

    Alibaba

    Qwen is a powerful, free AI assistant built on the advanced Qwen model series, designed to help anyone with creativity, research, problem-solving, and everyday tasks. While Qwen Chat is the main interface for most users, Qwen itself powers a broad range of intelligent capabilities including image generation, deep research, website creation, advanced reasoning, and context-aware search. Its multimodal intelligence enables Qwen to understand and process text, images, audio, and video simultaneously for richer insights. Qwen is available on web, desktop, and mobile, ensuring seamless access across all devices. For developers, the Qwen API provides OpenAI-compatible endpoints, making integration simple and allowing Qwen’s intelligence to power apps, services, and automation. Whether you're chatting through Qwen Chat or building with the Qwen API, Qwen delivers fast, flexible, and highly capable AI support.
    Starting Price: Free
  • 3
    Gemini 1.5 Pro
    The Gemini 1.5 Pro AI model is a state-of-the-art language model designed to deliver highly accurate, context-aware, and human-like responses across a variety of applications. Built with cutting-edge neural architecture, it excels in natural language understanding, generation, and reasoning tasks. The model is fine-tuned for versatility, supporting tasks like content creation, code generation, data analysis, and complex problem-solving. Its advanced algorithms ensure nuanced comprehension, enabling it to adapt to different domains and conversational styles seamlessly. With a focus on scalability and efficiency, the Gemini 1.5 Pro is optimized for both small-scale implementations and enterprise-level integrations, making it a powerful tool for enhancing productivity and innovation.
  • 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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