LLMChat.me is an online service that aggregates dozens of open-source large language models into a unified chat interface. Users can select from models such as Vicuna, Alpaca, ChatGLM, and MOSS to generate text, code, or creative content. The platform stores conversation history, supports custom system prompts, and allows seamless switching between different model backends. Ideal for experimentation, prototyping, and productivity, LLMChat.me runs entirely in the browser without downloads, offering fast, secure, and free access to leading community-driven AI models.

LLPhant is an open-source Python framework enabling developers to create versatile LLM-driven agents. It offers built-in abstractions for tool integration (APIs, search, databases), memory management for multi-turn conversations, and customizable decision loops. With support for multiple LLM backends (OpenAI, Hugging Face, others), plugin-style components, and configuration-driven workflows, LLPhant accelerates agent development. Use it to prototype chatbots, automate tasks, or build digital assistants that leverage external tools and contextual memory without boilerplate code.

LLM State Machine is an open-source Python framework designed to construct AI agents using explicit state machines. Developers define states as discrete steps—each invoking a large language model or custom logic—and transitions based on outputs. This approach provides clarity, maintainability, and robust error handling for multi-step, LLM-powered workflows, such as document processing, conversational bots, or automation pipelines.

Llamator is an open-source JavaScript library that enables developers to build autonomous AI agents by combining memory modules, tool integrations, and dynamic prompt templates in a unified pipeline. It orchestrates planning, action execution, and reflection loops to handle multi-step tasks, supports multiple LLM providers, and allows custom tool definitions for API calls or data processing. With Llamator, you can rapidly prototype chatbots, personal assistants, and automated workflows within web or Node.js applications, leveraging a modular architecture for easy extension and testing.

LLMs provides a unified abstraction over various open-source and hosted language models, allowing developers to load and run models through a single interface. It supports model discovery, prompt and pipeline management, batch processing, and fine-grained control over tokens, temperature, and streaming. Users can easily switch between CPU and GPU backends, integrate with local or remote model hosts, and cache responses for performance. The framework includes utilities for prompt templates, response parsing, and benchmarking model performance. By decoupling application logic from model-specific implementations, LLMs accelerates the development of NLP-powered applications such as chatbots, text generation, summarization, translation, and more, without vendor lock-in or proprietary APIs.

Web LLM Assistant is a lightweight open-source framework that transforms your browser into an AI inference platform. It leverages WebGPU and WebAssembly backends to run LLMs directly on client devices without servers, ensuring privacy and offline capability. Users can import and switch between models such as LLaMA, Vicuna, and Alpaca, chat with the assistant, and see streaming responses. The modular React-based UI supports themes, conversation history, system prompts, and plugin-like extensions for custom behaviors. Developers can customize the interface, integrate external APIs, and fine-tune prompts. Deployment only requires hosting static files; no backend servers are needed. Web LLM Assistant democratizes AI by enabling high-performance local inference in any modern web browser.

Dagger LLM is a suite of AI-powered features that leverages state-of-the-art large language models to streamline DevOps pipeline development. Users describe desired CI/CD flows in natural language, and Dagger LLM translates these prompts into complete pipeline definitions, supporting multiple languages and frameworks. It offers on-the-fly code suggestions, optimization recommendations, and context-aware adjustments. With built-in intelligence for debugging and refactoring, teams can quickly iterate on pipelines, enforce best practices, and maintain consistency across complex container-based deployments.

llm-tournament provides a modular, extensible approach for benchmarking large language models. Users define participants (LLMs), configure tournament brackets, specify prompts and scoring logic, and run automated rounds. Results are aggregated into leaderboards and visualizations, enabling data-driven decisions on LLM selection and fine-tuning efforts. The framework supports custom task definitions, evaluation metrics, and batch execution across cloud or local environments.

LLM Functions provides a simple framework to bridge large language model responses with real code execution. You define functions via JSON schemas, register them with the library, and the LLM will return structured function calls when appropriate. The library parses those responses, validates the parameters, and invokes the correct handler. It supports synchronous and asynchronous callbacks, custom error handling, and plugin extensions, making it ideal for applications that require dynamic data lookup, external API calls, or complex business logic within AI-driven conversations.

LLM Text Summarizer is a Chrome extension that uses advanced AI from OpenAI to produce high-quality summaries of selected text. Users can simply select the text they want summarized, right-click, and choose 'Summarize' from the context menu. The extension processes the text with OpenAI's API and provides a concise summary in a modal window. The summary can be easily copied to the clipboard, and the tool supports Markdown for better readability. It is customizable with personal OpenAI API keys.

LLM Prompt Saver is an intuitive Chrome extension that enhances your interactions with various Language Learning Models (LLMs) such as ChatGPT, Claude, CoPilot, and Gemini. The extension lets you save, manage, and reuse up to five prompts per LLM, making it easier to maintain consistency and productivity in your AI interactions. With a clean interface and a large text area for comfortable editing, you can effortlessly switch between LLMs, save new prompts, and manage your saved prompts with options to copy, load for editing, or delete as needed. This tool is ideal for researchers, writers, developers, and frequent LLM users who seek to streamline their workflow.

Awan LLM is an innovative language model API provider that delivers unlimited token generation without the usual per-token costs, making it a highly economical choice for developers and businesses. It caters to a universal user base, enabling seamless integration into various applications. The platform's architecture is designed for reliability and accessibility, allowing users to leverage advanced AI technologies easily and efficiently. Whether you’re developing chatbots, automated content creation tools, or intelligent systems, Awan LLM ensures you have the resources needed for scalable performance.

LiteLLM is a comprehensive framework designed to streamline the management of multiple large language models (LLMs) through a unified API. By offering a standardized interaction model similar to OpenAI’s API, users can easily leverage over 100 different LLMs without dealing with diverse formats and protocols. LiteLLM handles complexities like load balancing, fallbacks, and spending tracking across different service providers, making it easier for developers to integrate and manage various LLM services in their applications.

LLM Price Check is a specialized tool designed to help users easily compare the pricing of various Large Language Models (LLMs) APIs across key providers. It features a comprehensive pricing calculator that allows users to explore detailed costs, quality scores, and potential free trial options. Whether you’re looking to compare OpenAI’s GPT-4, Google's Gemini, or AWS’s Mistral, LLM Price Check offers up-to-date pricing information to aid in making informed decisions.

0LLM provides a robust, scalable platform for developing and managing large-scale language models. It is equipped with advanced tools and features that facilitate seamless integration, model training, and deployment. 0LLM aims to streamline the process of creating powerful AI-driven solutions by offering an intuitive interface, comprehensive support, and enhanced performance. Its primary goal is to empower developers and enterprises in harnessing the full potential of AI and language models.

OpenPlayground is an open-source platform that allows users to experiment with and compare different large language models (LLMs). It's designed to help users understand the strengths and weaknesses of various LLMs by providing a user-friendly and interactive environment. The platform can be particularly useful for developers, researchers, and anyone interested in the capabilities of artificial intelligence. Users can sign up easily using their Google account or email.

LLMOps.Space serves as a dedicated community for practitioners interested in the intricacies of deploying and managing large language models (LLMs) in production environments. The platform emphasizes standardized content, discussions, and events to meet the unique challenges posed by LLMs. By focusing on practices like fine-tuning, prompt management, and lifecycle governance, LLMOps.Space aims to arm its members with the knowledge and tools necessary to scale and optimize LLM deployments. It also features educational resources, company news, open-source LLM modules, and much more.

LLM Optimize is a cutting-edge platform designed to help businesses optimize their websites for AI-driven search engines. By providing actionable audits, the platform identifies areas for improvement, helping you achieve higher visibility in generative AI models like ChatGPT and Google's AI Overview. With its user-friendly interface, LLM Optimize streamlines the optimization process, ensuring you stay ahead in the ever-evolving digital landscape.

OpenLIT is an advanced observability tool tailored for GenAI and LLM applications. By leveraging OpenTelemetry, it combines traces and metrics into a single interface, allowing developers to monitor performance, user interactions, and resource usage effectively. Its auto-instrumentation supports various LLM frameworks and VectorDBs, offering valuable insights into application behavior. OpenLIT is designed to help teams optimize their LLM deployments and understand cost implications.

LM Studio is an innovative platform designed for AI enthusiasts, developers, and data scientists to explore, download, and utilize open-source large language models (LLMs) locally. Its seamless functionality supports various AI interactions, making it ideal for both casual users and advanced professionals. Notably, LM Studio operates entirely offline, allowing users to leverage AI without internet dependency. The application features a chat interface for easy interaction and is compatible with models from different sources, ensuring versatility in usage. Whether you want to analyze data, create applications, or just experiment with AI, LM Studio has you covered.