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Auto-detect hardware and recommend the best Gemma 4 model for local deployment on PC, Mac, or mobile.
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Based on SOC occupation classification
| 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 |
Find the best Gemma 4 model for your hardware in seconds.
Website: https://www.gemmamatch.com
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.
| 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 |
