3 projects for "macbook" with 1 filter applied:

  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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  • Build Data Resilience - Take the Assessment Today Icon
    Build Data Resilience - Take the Assessment Today

    Can you recover when it matters most? Take this quick assessment to identify gaps and build greater recovery confidence.

    Is your recovery strategy as strong as you think? Take this quick self-assessment to check your recovery readiness and gain tailored insights. In only 2 minutes, you'll learn where you fall on the recovery readiness scale.
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  • 1
    TurboFieldfare

    TurboFieldfare

    Gemma 4 26B-A4B inference in ~2 GB of RAM on any M-series MacBook

    TurboFieldfare is a custom Swift and Metal runtime for running the instruction-tuned Gemma 4 26B-A4B model on Apple Silicon Macs with limited memory. Instead of loading the entire model, it keeps the shared core and KV cache in RAM while streaming only the routed experts required for each token from SSD. This approach reduces active memory use to roughly 2 GB while the installed model occupies about 14.3 GB of storage. The project includes a native Mac application, command-line tools, a...
    Downloads: 4 This Week
    Last Update:
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  • 2

    punykit

    PunyKit - it's a very simple webkit-based browser.

    ...What I'm aiming for is something that is as close to the iPhone simulator as possible, but with a web-inspector and (Yay!) works on machines which weren't made by the Apple corporation. Still early days and (ironically) I wrote it to use on my MacBook, but hey. It's good.
    Downloads: 0 This Week
    Last Update:
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  • 3
    Ling 3.0 Tiny

    Ling 3.0 Tiny

    Lightweight MoE model for local reasoning, coding, and AI agents

    ...It is specifically optimized for local and resource-constrained deployment and has been validated on NVIDIA DGX Spark, Apple Silicon MacBooks, and Mac mini systems. FP8 testing reached around 100–105 tokens/s on DGX Spark and 86–90 tokens/s on an M4 Pro MacBook. BF16, FP8, and INT4 weights are available, while deployment options include SGLang, vLLM, and experimental Ollama support on Apple Silicon.
    Downloads: 0 This Week
    Last Update:
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