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Gemma 4

Source reports covering Gemma 4. Stories will appear when analysis and community reactions are ready.

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Source reports

  • Running Gemma 4 26B at 5 tokens/sec on a 13-year-old Xeon with no GPU

    tool

    10 min read

    Gemma 4, a 26-billion-parameter open-weights mixture-of-experts model, runs on a 13-year-old Xeon server without a GPU at a speed of approximately five tokens per second. The server is a repurposed HP StoreVirtual storage box originally designed for disk storage.

    LLMsAI hardwareMachine learning

  • Gemma 4 QAT models: Optimizing compression for mobile and laptop efficiency

    tool

    4 min read

    Gemma 4 has introduced Multi-Token Prediction (MTP) to enhance inference speed. New checkpoints optimized with Quantization-Aware Training (QAT) have been released to improve efficiency for mobile and laptop use.

    Model compressionAI efficiencyDeveloper tools

  • Accelerating Gemma 4: faster inference with multi-token prediction drafters

    tool

    4 min read

    Gemma 4 now features Multi-Token Prediction (MTP) drafters, enhancing inference speed and efficiency. This update aims to improve performance across developer workstations, mobile devices, and cloud environments.

    LLMsDeveloper toolsAI efficiency

  • Google Gemma 4 Runs Natively on iPhone with Full Offline AI Inference

    tool

    2 min read

    Google's Gemma 4 model family now runs natively on iPhones, enabling full local AI inference offline. Early benchmarks show the 31B variant of Gemma 4 performing comparably to Qwen 3.5's 27B model.

    Edge AIOn device AIGoogle

  • I ran Gemma 4 as a local model in Codex CLI

    tool

    7 min read

    Gemma 4 was tested as a local model in Codex CLI to determine its viability as a replacement for cloud models in coding tasks. The testing involved using a 24 GB M4 Pro MacBook Pro to evaluate Gemma 4's local tool calling capabilities.

    Codex cliLocal AI modelsCode generation

  • April 2026 TLDR Setup for Ollama and Gemma 4 26B on a Mac mini

    tool

    4 min read

    Ollama can be installed on a Mac mini with Apple Silicon using Homebrew with the command `brew install --cask ollama-app`, which includes auto-updates and the MLX backend. A minimum of 16GB of unified memory is required for running Gemma 4, and the Ollama app will appear in the Applications folder and the menu bar after installation.

    OllamaApple siliconDeveloper tools

  • Google releases Gemma 4 open models

    tool

    1 min read

    Gemma 4 delivers maximum compute and memory efficiency for mobile and IoT devices, enhancing intelligence in these platforms. It supports the development of autonomous agents capable of planning, navigating apps, and completing tasks, while also offering strong audio and visual understanding for rich multimodal applications and multilingual experiences that extend beyond simple translation.

    AI agentsMultimodal AIMobile AI
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