There’s a new AI trend where people are merging games, and the results look incredible. Legal and technical issues aside, this article explains how AI is being used to merge games and whether local AI can take the whole load or at least share some of it.
I’ve seen examples including Minecraft-style systems inside Elden Ring, Skate-style gameplay inside Modern Warfare 2, even the Minecraft Nether inside GTA 5, and other projects where modders use large cloud models to help connect completely different game systems together.
These projects are usually not literally combining two full games into one file, but they are getting much closer to what people imagine when they hear “merging games.”
Cloud AI models are especially good at this kind of work because they can handle large amounts of code, long conversations, debugging, and complicated reasoning across different systems. A modder can give the model scripts, error logs, decompiled code, API documentation, and other project files, then use it as a coding assistant throughout the whole process.
Cloud AI has already proven useful for coding, so the more interesting question is whether local AI models can handle the same workload on consumer-level hardware or if that is still mostly a dream.
AI Makes Modding Much Faster
Game modding is already pretty popular among players. I’m sure many players of Skyrim or The Sims have downloaded at least one mod.
Mods are not just useful for adding new features. They are also great for improving graphics, character models, animations, and cinematics. For example, the Androids Remastered mod made the characters in NieR:Automata look far better with a single install.
With AI, you can move through parts of the modding process much faster. It can inspect code, explain decompiled functions, write scripts, fix errors, and suggest how a new feature could be implemented.
If the game already has proper modding tools or source code available, things become much easier because you can skip a lot of the reverse-engineering work.
Of course, saying AI can fully reverse engineer a game, add a feature, and package everything in a day would be pushing it. For smaller features or games with good modding support, though, AI can definitely make the process much faster than doing everything manually.
Where Local AI Struggles
Local AI can technically do the same type of work, but this is where things get harder. A local coding model can read code, explain functions, debug scripts, analyze logs, and help write new features.
You can also connect it directly to your editor, terminal, file system, modding tools, and other parts of your development workflow.
The problem is that cloud models run on remote servers with massive hardware behind them, while local models have to work with whatever CPU, GPU, RAM, and VRAM you have inside your own machine.
And yes, game files are complicated as hell. Reverse engineering can involve decompiled functions, unknown variables, memory addresses, scripts, logs, and hundreds of systems connected to each other.
A model needs enough context to understand how those pieces fit together, and this is where larger cloud models usually have an advantage because they can handle more context and generally have stronger reasoning for complicated codebases.
Local models can still help, but you may need to break the project into smaller pieces instead of giving the model a massive part of the game at once.
You can also use smaller or quantized models and only provide the files that actually matter. That makes local AI much more practical, but there is still a point where the workload becomes too large for normal consumer hardware.
So the problem is not that local AI cannot code. The real problem is how much of the project your hardware can let the model understand at once.
Local AI Still Has Advantages
The biggest advantage is privacy because you can keep your code, decompiled files, scripts, logs, and other project data on your own computer instead of sending them to an external service.
That matters more than it sounds. Logs, configuration files, save data, and file paths can include details about your computer or user account, so blindly uploading entire folders to a cloud service is not a good idea.
You can also work offline and connect the model directly to your own tools and scripts, which gives you much more control over the workflow.
Legal Basis and Limitations
There is also a legal side to all of this. Reverse engineering is not automatically illegal, but what you are allowed to do depends on where you live, what you are doing, and how the game is protected.
For example, both the U.S. and EU allow reverse engineering or decompiling software in some situations, especially when developers need it to make independently created software work with another program.
That does not mean you can reverse engineer any game however you want. Copyright rules, game license terms, DRM protections, and other restrictions can still apply.
There is also a big difference between recreating a mechanic and copying actual game content. Rebuilding a movement system or making something work in a similar way is very different from redistributing source code, maps, music, character models, or other copyrighted files.
AI makes the technical side faster, but it does not change the legal rules. This is general information, not legal advice. Just because AI can help copy or rebuild something does not mean you automatically have the right to share it.
The easier route is working with games that officially support mods, provide APIs or SDKs, or have clear modding rules. Once DRM bypassing, leaked source code, or copied game assets get involved, things become much more complicated.
Conclusion
Cloud AI models will probably lead this kind of work for now because they have access to stronger hardware, larger models, longer context, and better reasoning for complicated projects.
Local AI is not ready to take the entire load for most users, but it can definitely share part of it. Smaller, repetitive tasks like explaining functions, inspecting logs, debugging scripts, and working with local development tools suit it well, while cloud models handle the really heavy parts.
