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Dev tools · April 10, 2026

Gemma 4 Local Hardware Matcher

Auto-detects your hardware to recommend the best Gemma 4

What it does

Stop guessing VRAM requirements. Run Gemma 4 local with auto GPU detection — get the exact model, quantization, and run command for your PC, Mac, iPhone, or Android.

Does the same job

all alternatives →
  • OS
    Open-source engine running Gemma 4 26B in 2 GB RAM on any M-series MacJul 2026 · github.com · ▲919

    Hi HN, I built a specialized inference engine for running 4-bit Gemma 4 26B-A4B-IT on any M-series Mac using about 2 GB of RAM. It is called TurboFieldfare and is written in Swift and Metal. I have always adored on-device AI. It feels like magic that you can run a powerful NN on your Mac or iPhone. So I wanted to push the limits a bit and run a model whose weights don’t fit in memory. The model’s 4-bit quantized weights occupy roughly 14 GB, which makes running it with conventional inference tools almost impossible on an 8 GB or even 16 GB Mac once the OS, applications, and KV cache are…

  • Google Gemma 4 12BJun 2026 · blog.google · ▲310

    Run multimodal AI locally with an encoder-free architecture

  • IM
    I made a Gemma 4 Mac app that names screenshots with local AIMay 2026 · snapname.app · ▲7

    I made my first macOS utility app that ships with a bundled Gemma 4 model, specifically the Gemma E4B one. It made my app DMG have 5.3 GB in size, but I think it is a small size for the power that this free local model can provide. It runs fine on CPU, but can also run on Apple Silicon GPU, although I did not notice any performance improvements with GPU (tested on a M5 chip). I think these local lightweight and multimodal models will open multiple possibilities for new software tools where privacy is essential.

  • Google Gemma 4Apr 2026 · blog.google · ▲440

    Google's most intelligent open models to date

  • G4
    Gemma 4 Multimodal Fine-Tuner for Apple SiliconApr 2026 · github.com · ▲235

    About six months ago, I started working on a project to fine-tune Whisper locally on my M2 Ultra Mac Studio with a limited compute budget. I got into it. The problem I had at the time was I had 15,000 hours of audio data in Google Cloud Storage, and there was no way I could fit all the audio onto my local machine, so I built a system to stream data from my GCS to my machine during training. Gemma 3n came out, so I added that. Kinda went nuts, tbh. Then I put it on the shelf. When Gemma 4 came out a few days ago, I dusted it off, cleaned it up, broke out the Gemma part from the Whisper…

  • Gemma 3n2025 · ▲199

    Run powerful multimodal AI right on your phone

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