Which stack should i use for mobile puzzle game? That ai can see and play

GPT-5.5

Vote: unity

I would choose A: unity. For a mobile puzzle game, Unity has the strongest overall stack: mature Android/iOS export, good UI tools, lots of plugins, and a large ecosystem for ads, analytics, in-app purchases, and testing. For the requirement that AI can see and play, Unity is also the best fit because it has Unity ML-Agents, easy access to game state, camera/render textures, screenshots, and automation hooks. You can let an AI play from raw pixels, from structured game state, or from a custom API depending on how realistic you want the AI interaction to be. B: godot is a good lightweight choice, especially for 2D puzzles, but the mobile and AI tooling ecosystem is smaller. C: phaser is great for browser games, but for a polished mobile app with AI integration, it is usually less convenient than Unity.

Claude Opus 4.7

Vote: unity

For a mobile puzzle game where an AI needs to 'see and play' it, Unity is the strongest choice. Unity has the most mature mobile deployment pipeline (iOS/Android), and critically, it has the best ecosystem for AI integration: ML-Agents is a first-class framework for training agents that observe game state and act, and there are robust tools for headless simulation, frame capture, and scripted input injection. Godot is improving but has weaker mobile tooling and no equivalent to ML-Agents. Phaser is a web/JS framework — fine for browser puzzles, but mobile packaging (via Cordova/Capacitor) is clunky and there's no standard AI-agent harness; you'd be hand-rolling DOM/canvas scraping. If the AI needs structured observations (board state) Unity lets you expose them directly to a Python trainer; if it needs pixel input, Unity's render-to-texture + ML-Agents visual observations handle that out of the box. That makes Unity the most pragmatic stack for 'AI that can see and play.'

Gemini 3.1 Pro

Vote: unity

Unity is widely regarded as the industry standard for both mobile game development and AI game integration. The primary reason to choose Unity for a project where an AI needs to 'see and play' is the Unity Machine Learning Agents Toolkit (ML-Agents). ML-Agents is a highly mature, first-party framework that allows you to turn your game into an environment for training intelligent agents. It provides built-in sensors (like Ray Perception Sensors and camera observations) that allow the AI to 'see' the game state, and action buffers to let the AI control the game. While Godot has community-driven plugins (like Godot RL Agents) and Phaser allows JavaScript-based AI integrations, neither comes close to the production readiness, extensive documentation, and large community support of Unity ML-Agents. Furthermore, Unity provides excellent cross-platform compilation, making it incredibly straightforward to deploy your puzzle game to mobile devices once the AI is trained.

Grok 4.3

Vote: unity

Unity offers the strongest support for mobile deployment alongside robust AI integration via ML-Agents, allowing the AI to observe and interact with the puzzle game environment effectively. Godot is capable for 2D puzzles but has fewer mature AI tooling options compared to Unity. Phaser is web-focused and less suitable for native mobile performance or advanced AI vision features.

Final Summary

The AI Roundtable reached a swift and unanimous consensus, with all four models identifying Unity as the definitive choice for an AI-integrated mobile puzzle game. GPT-5.5, Claude Opus 4.7, Gemini 3.1 Pro, and Grok 4.3 all pointed to the Unity ML-Agents toolkit as the decisive factor, noting its superior ability to let an AI 'see' through camera sensors and 'act' via mature input hooks.

No agreement after 1 rounds of discussion. Final vote: unity: 4

Strongest Arguments

• unity: Unity is the clear winner due to its ML-Agents toolkit, which offers a first-party, production-ready framework for training intelligent agents to observe game states and interact with them out of the box.