Gemma Gem vs Rowboat

Gemma Gem is an open-source Chrome extension that runs Google's Gemma 4 language model entirely in your browser using WebGPU — no API keys, no server, no data leaving your device. Install the extension, wait for the one-time model download (500MB for the efficient 2B variant, 1.5GB for the larger 4B), and you have a fully private AI assistant that can read web pages, fill forms, take screenshots, and execute JavaScript. The extension uses Hugging Face Transformers.js with ONNX-quantized versions of Gemma 4's E2B and E4B variants, making the model small enough to run in a browser tab without throttling GPU memory. Gemma 4's strong efficiency profile — particularly its per-layer attention architecture — makes it a natural fit for WebGPU's memory constraints compared to older models at similar parameter counts. What makes Gemma Gem interesting beyond the cool factor: it's a glimpse at what fully private, zero-latency browser-native AI looks like. There's no round-trip to a server, no API billing, no rate limits. On a mid-range MacBook M3 or gaming GPU, inference is fast enough to be genuinely useful. The trade-off is capability — Gemma 4 E2B is a 2B parameter model, not Claude or GPT-5, but for summarization, form-filling, and basic Q&A it holds its own.

Rowboat is a local-first, open-source AI coworker that connects to your email and meeting notes, builds a persistent Obsidian-compatible knowledge graph from them, and uses that context to draft documents, meeting briefs, slide decks, and emails. It works with local models via Ollama or LM Studio, or with hosted APIs, and supports MCP for connecting external tools. The design philosophy is deliberately anti-cloud: all data stays in plain text Markdown files you can read, grep, and version-control. The knowledge graph is transparent — you can open it in Obsidian and see exactly what the AI knows about you. No black-box embeddings in a proprietary vector store, no "trust us with your emails" data agreements. Rowboat implements what Karpathy described as a "long-term memory coworker" — an AI that compounds value over time because it actually knows your history, your projects, and your terminology. TypeScript codebase, Apache 2.0 license, surging on GitHub trending this week.