Google AI Edge Gallery vs Mediator.ai

Google AI Edge Gallery is a mobile app that lets anyone run powerful open-source LLMs — primarily Gemma 4 — directly on their Android or iOS device with zero internet connectivity. The April 2026 update brought full Gemma 4 support including the E2B edge variant optimized for sub-1.5GB RAM, alongside new Agent Skills that enable multi-step autonomous workflows entirely on-device. The app goes well beyond a chat interface. Users get Thinking Mode to watch the model's reasoning process in real time, multimodal features for image analysis and voice transcription, a Prompt Lab for experimentation, and Tiny Garden — an interactive game driven purely by on-device natural language understanding. Hugging Face integration lets users import custom models beyond the curated defaults. The significance of the April 7 release is timing: it dropped the same day as LiteRT-LM and coincides with Gemma 4's general availability, creating a complete stack from framework to end-user app. With 899 GitHub stars gained in a single day and app store availability on both iOS and Android, Edge Gallery is becoming the reference showcase for what on-device AI looks like in 2026.

Mediator.ai applies LLMs and Nash bargaining theory to real-world disputes, generating agreements that both parties would accept — including solutions neither side had imagined independently. The process is private by design: each party separately describes their position, priorities, and constraints. The AI then generates multiple candidate agreements, scores each one against both parties' stated needs, and iteratively refines proposals until reaching an optimal solution. Use cases range from founder equity disputes and contractor payment conflicts to shared housing arrangements and inheritance disagreements. The system's key insight is that human negotiation is systematically bad at identifying the entire solution space — we anchor on positions, not interests. By modeling both parties' utility functions simultaneously, the AI can find Pareto-optimal outcomes that pure adversarial negotiation often misses entirely. With 159 Hacker News points, the response was genuinely enthusiastic — and the concept is hard to dismiss. Nash bargaining as a formalism has decades of academic credibility; what's new is making it accessible via natural language input. The pricing isn't published yet and the team is small, but the application domain (legal, HR, personal disputes) is enormous if they can nail trust and confidentiality.