Gemma4local
Skill walex8925/Gemma4local
Auto-detect hardware and recommend the best Gemma 4 model for local deployment on PC, Mac, or mobile.From its SKILL.md
npx -y skills add walex8925/Gemma4localAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
2.3 KB, 512 tokens by cl100k_base, as published. Nobody here has run it
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
- Visit https://www.gemmamatch.com
- Allow hardware detection (or enter specs manually)
- Get your recommended model + run command
- 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
What ships with it: 1 file
3.3 KB alongside SKILL.md
- README.md3.3 KB