Showing 2 open source projects for "edge computing"

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    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

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  • 1
    mllm

    mllm

    Fast Multimodal LLM on Mobile Devices

    mllm is an open-source inference engine designed to run multimodal large language models efficiently on mobile devices and edge computing environments. The framework focuses on delivering high-performance AI inference in resource-constrained systems such as smartphones, embedded hardware, and lightweight computing platforms. Implemented primarily in C and C++, it is designed to operate with minimal external dependencies while taking advantage of hardware-specific acceleration technologies such as ARM NEON and x86 AVX2 instructions. ...
    Downloads: 1 This Week
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  • 2
    nndeploy

    nndeploy

    An Easy-to-Use and High-Performance AI Deployment Framework

    ...The framework focuses on making it easier to transform trained AI models into production-ready applications that can run efficiently on desktops, mobile devices, servers, and edge computing hardware. Developers can use visual workflows to design and configure AI processing pipelines by connecting modular nodes that represent different stages of the inference process. The system supports multiple inference engines and hardware accelerators, allowing the same AI workflow to run on different platforms without significant modifications. nndeploy also includes performance optimization techniques such as parallel execution, memory reuse, and hardware-accelerated operations to improve inference speed.
    Downloads: 0 This Week
    Last Update:
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