2 projects for "edge computing" with 2 filters applied:

  • $300 Free Credits to Build on Google Cloud Icon
    $300 Free Credits to Build on Google Cloud

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  • Host LLMs in Production With On-Demand GPUs Icon
    Host LLMs in Production With On-Demand GPUs

    NVIDIA L4 GPUs. 5-second cold starts. Scale to zero when idle.

    Deploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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  • 1
    PicoLM

    PicoLM

    Run a 1-billion parameter LLM on a $10 board with 256MB RAM

    ...The runtime is capable of running language models with billions of parameters on devices with only a few hundred megabytes of memory, which is significantly lower than typical LLM infrastructure requirements. This makes PicoLM particularly suitable for edge computing, offline AI applications, and embedded AI devices that cannot rely on cloud resources.
    Downloads: 1 This Week
    Last Update:
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  • 2
    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
    Last Update:
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