GemmaMatch — Gemma 4 Local Hardware Matcherv1.0.0

A user with a phone or tablet wants to run Gemma 4 locally for on-device inference. GemmaMatch detects limited VRAM and recommends the E2B tier with a copy-paste run command.

A developer with an 8-16 GB VRAM GPU uses GemmaMatch to get a tailored Ollama command for the 26B MoE model, enabling fast coding assistance without cloud dependency.

A researcher with 24+ GB VRAM seeks high-quality generation. GemmaMatch recommends the 31B Dense model and provides platform-specific setup guides for Linux with CUDA.

An IT admin needs to standardize Gemma 4 deployment across diverse employee hardware. GemmaMatch auto-detects each machine and outputs appropriate run commands for macOS, Windows, and Linux.

A gamer considering a GPU upgrade uses GemmaMatch's manual comparison mode to evaluate which Gemma 4 tier they could run after upgrading, comparing VRAM scenarios.

Basic matching is free. Premium subscribers get detailed hardware benchmark comparisons, upgrade recommendations, and priority access to new model tiers.

Partner with GPU retailers, cloud providers, and hardware manufacturers. When users upgrade based on recommendations, GemmaMatch earns a commission.

Provide an API for organizations to integrate GemmaMatch into their internal deployment pipelines, matching models to thousands of managed devices automatically.