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Artificial Intelligence Software
Artificial Intelligence (AI) software is computer technology designed to simulate human intelligence. It can be used to perform tasks that require cognitive abilities, such as problem-solving, data analysis, visual perception and language translation. AI applications range from voice recognition and virtual assistants to autonomous vehicles and medical diagnostics.
AI Models
AI models are systems designed to simulate human intelligence by learning from data and solving complex tasks. They include specialized types like Large Language Models (LLMs) for text generation, image models for visual recognition and editing, and video models for processing and analyzing dynamic content. These models power applications such as chatbots, facial recognition, video summarization, and personalized recommendations. Their capabilities rely on advanced algorithms, extensive training datasets, and robust computational resources. AI models are transforming industries by automating processes, enhancing decision-making, and enabling creative innovations.
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    Atomic Agent

    Atomic Agent

    Atomic Agent

    Atomic Agent is an open-source, local-first AI agent that runs on your own machine from the terminal. It drives your real tools — shell, files, and browser — and keeps every session on your own disk. Point it at a local model through llama.cpp, or connect a hosted model when you want more power. You choose the model, you own the data, you stay in control. No cloud lock-in. Install with a single command on macOS, Linux, or Windows. Built for developers and power users who want a capable autonomous agent without shipping their work to someone else's cloud.
    Starting Price: $0
  • 2
    MindMac

    MindMac

    MindMac

    ...It supports multiple AI providers, including OpenAI, Azure OpenAI, Google AI with Gemini, Gemini Enterprise Agent Platform, Anthropic Claude, OpenRouter, Mistral AI, Cohere, Perplexity, OctoAI, and local LLMs via LMStudio, LocalAI, GPT4All, Ollama, and llama.cpp. MindMac offers over 150 built-in prompt templates to facilitate user interaction and allows for extensive customization of OpenAI parameters, appearance, context modes, and keyboard shortcuts. The application features a powerful inline mode, enabling users to generate content or ask questions within any application without switching windows. ...
    Starting Price: $29 one-time payment
  • 3
    EXAONE Deep
    ...The repository provides comprehensive documentation covering performance evaluations, quickstart guides for using EXAONE Deep models with Transformers, explanations of quantized EXAONE Deep weights in AWQ and GGUF formats, and instructions for running EXAONE Deep models locally using frameworks like llama.cpp and Ollama.
    Starting Price: Free
  • 4
    LFM2.5

    LFM2.5

    Liquid AI

    ...The LFM2.5 family includes Base (for fine-tuning and customization), Instruct (general-purpose instruction-tuned), Japanese-optimized, Vision-Language, and Audio-Language variants, all optimized for fast, on-device inference under tight memory constraints and available as open-weight models deployable via frameworks like llama.cpp, MLX, vLLM, and ONNX.
    Starting Price: Free
  • 5
    Laguna XS 2.1
    ...It is served with a 256K context window, giving agents room to work with large codebases, lengthy histories, and multi-step workflows. Laguna XS 2.1 is supported by vLLM, SGLang, NVIDIA TensorRT-LLM, Hugging Face Transformers, and Ollama, with native llama.cpp support planned. It is available in BF16, FP8, INT4, and NVFP4 checkpoints, allowing developers to choose between maximum fidelity and configurations suited to tighter VRAM or compute budgets.
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    BaseRT

    BaseRT

    Base Compute

    ...Accelerated by hand-written Metal kernels, it is designed to deliver fast prefill and decode performance on M-series Macs, with published benchmarks showing up to 6.4× faster prefill than llama.cpp, 3.9× faster than MLX, and up to 1.33× faster decode. The basert CLI handles model downloading, conversion, interactive chat, serving, completion, benchmarking, inspection, and bundle signing. Its server supports chat, completions, embeddings, transcription, tool calls, continuous batching, paged KV caching, and prefix caching, while supported models can process text, vision, and audio. ...
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