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GemmaMatch — Gemma 4 Local Hardware Matcher

该 Skill 以说明文档形式介绍 GemmaMatch:通过 WebGPU/WebGL 检测或手动输入硬件规格,推荐 Gemma 4 E2B、26B MoE 或 31B Dense,并给出 Ollama/LM Studio 等运行命令和平台设置指引;材料未包含实际检测或安装代码。

walex8925
walex8925
热度 41.20
最近更新 2026-05-11 17:42:44
分类:开发依赖:联网浏览搜索应用场景:推荐 / 工作流 / DevOps

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add gemmamatch
Metadata
name
gemmamatch
description
Auto-detect hardware and recommend the best Gemma 4 model for local deployment on PC, Mac, or mobile.
author
GemmaMatch
version
1.0.0
keywords
["gemma4","local-llm","hardware-matcher","ollama","gpu-detection"]
homepage
https://www.gemmamatch.com
source
https://github.com/walex8925/Gemma4local

GemmaMatch — Gemma 4 Local Hardware Matcher

Find the best Gemma 4 model for your hardware in seconds.

Website: https://www.gemmamatch.com

What it does

GemmaMatch auto-detects your GPU, VRAM, and system specs via WebGPU/WebGL APIs, then recommends the most suitable Gemma 4 model tier and provides a ready-to-use run command. All processing happens locally in your browser — no data leaves your device.

Recommended model tiers

Tier Target hardware Use case
Gemma 4 E2B Phones, tablets, low-VRAM devices On-device inference, edge deployment
Gemma 4 26B MoE Desktop GPUs (8-16 GB VRAM) General local AI, coding assistance
Gemma 4 31B Dense Workstations (24+ GB VRAM) High-quality generation, research

Key features

  • Automatic GPU detection — uses WebGPU and WebGL APIs, no install required
  • Personalized model recommendation — matches your exact hardware to the optimal Gemma 4 variant
  • Platform-specific setup guides — step-by-step instructions for Mac (MLX, Ollama), Windows (Ollama, LM Studio), iOS, and Android
  • One-click run commands — get a copy-paste Ollama or LM Studio command tailored to your system
  • Manual comparison mode — compare upgrade scenarios or override auto-detection
  • Privacy-first — everything runs in-browser, zero data collection

Quick start

  1. Visit https://www.gemmamatch.com
  2. Allow hardware detection (or enter specs manually)
  3. Get your recommended model + run command
  4. Copy the command and run it in your terminal

Supported platforms

  • macOS — Apple Silicon (M1-M4), Intel with discrete GPU
  • Windows — NVIDIA (RTX 30/40/50 series), AMD (RX 7000 series)
  • Linux — NVIDIA CUDA, AMD ROCm
  • iOS / Android — on-device model recommendations

Links