Gemma 4 Agent Skills

The first native Swift inference engine for Gemma 4 on Apple Silicon / iOS

Gemma 4 31B Abliterated — quality-preserving guardrail removal for Google's most capable open model. Apache 2.0. Runs on Apple Silicon via MLX.

Autonomous AI Agent Skill for Google AI Edge Gallery - self-evolving, 100% offline

Personalize Gemma 4 and make it real-time on Apple Silicon. Fine-tune on your conversations, serve at 111 tok/s. No cloud required.

Run Gemma 4 locally with Gemma-4 Omni-Desktop. A free, offline AI agent optimized for RTX 30xx & 8GB Macs. Features native vision, voice & OpenClaw support.

Download the Gemma 4 Lightweight Installer. Run Google DeepMind's 26B MoE & 31B Dense models locally offline via llama.cpp with zero setup.

Claude Code Skills for building offline-capable AI features with Gemma 4 on-device LLM inference in Flutter apps. Includes scaffold templates, function calling guides, and reusable AI skill architecture.

Distributed systems for automated proposal generation. Orchestrates LLM agents for requirement extraction, semantic inventory matching, and competitive pricing analysis

Run Google Gemma 4 AI locally on your Mac. No internet, no subscriptions, no data leaves your device. Free forever.

Benchmark Gemma 4 E2B on Apple Silicon: MLX (mlx-lm) vs GGUF (llama-server), with TTFT, tokens/sec, and memory.

Drop-in KV cache compression for MLX on Apple Silicon. Brings PolarQuant (Google, ICLR 2026) to mlx-lm with first-class Gemma 4 support: MatFormer, dual head_dim, hybrid sliding/global attention, cross-layer KV sharing. 3-bit → 4.8× smaller cache, 0.995 logit cosine @ 4-bit.

Local multi-agent execution with middleware-level deduplication.

M.A.R.A. is a Multi-Agent Research Analyst. A self-correcting multi-agent research system built with LangGraph, Gemma 4, and Streamlit.

Hands-on benchmark of Google Gemma 4 in LM Studio, with prompts, Gradio evaluator, saved outputs, and a published companion report.

Practical local research and runtime toolkit for running Gemma 4 on a 24 GB M4 Pro

MacBook Air M2 24GB 한 대로 돌리는 Claude × 로컬 LLM 하이브리드 멀티-티어 오케스트레이션 — 컨셉·벤치마크·실전 셋업

Run Google's Gemma 4 entirely in your browser via WebGPU. Multimodal chat, E2B vs E4B arena, ONNX conversion toolkit.

Gemma-4-E4B-it running locally in a browser with WebGPU.

Agentic Coding MCP Server: Local Gemma 4 powered coding assistant integrated with Zed editor