alt Hacker NewsLLM models can not do spacial reasoning. I haven't tried with GPT, however, Claude can not solve a Rubik Cube no matter how much I try with prompt engineering. I got Opus 4.6 to get ~70% of the puzzle solved but it got stuck. At $20 a run it prohibitively expensive.
The point is if we can prompt an LLM to reason about 3 dimensions, we likely will be able to apply that to math problems which it isn't able to solve currently.
I should release my Rubiks Cube MCP server with the challenge to see if someone can write a prompt to solve a Rubik's Cube.
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> I should release my Rubiks Cube MCP server with the challenge to see if someone can write a prompt to solve a Rubik's Cube.
Do it, I'm game! You nerdsniped me immediately and my brain went "That sounds easy, I'm sure I could do that in a night" so I'm surely not alone in being almost triggered by what you wrote. I bet I could even do it with a local model!
Interesting (would like to hear more), but solving a Rubiks cube would appear to be a poor way to measure spatial understanding or reasoning. Ordinary human spatial intuition lets you think about how to move a tile to a certain location, but not really how to make consistent progress towards a solution; what's needed is knowledge of solution techniques. I'd say what you're measuring is 'perception' rather than reasoning.
What about a model designed for robotics and vision? Seems like an LLM trained on text would inherently not be great for this.
DeepMinds other models however might do better?
I bet I can even do it with the smallest gemma 4 model using a prompt of max 500 characters.
*yet
I’ve had a similar experience building a geometry/woodworking-flavored web app with Three.js and SVG rendering. It’s been kind of wild how quickly the SOTA models let me approach a new space in spatial development and rendering 3d (or SA optimization approaches, for that matter). That said, there are still easy "3d app" mistakes it makes like z-axis flipping or misreading coordinate conventions. But these models make similar mistakes with CSS and page awareness. Both require good verification loops to be effective.