I'm a college student, and I enjoy playing word games like Codenames, but it can be hard sometimes to find enough people to play when everyone is available, so I made an app that allows you to fill any seat with an AI teammate and also play against AI. This way it allows for people to get the full strategic experience of codenames just on their own.
Through this experiment, I was also able to measure and benchmark a few different LLMs through AWS Bedrock API calls and give them ELO ratings based on stuff like win rate and clue/guess accuracy. If anyone is interested, they can see more about my benchmarking methodology here: https://wordspies.com/hn#method. I think it's pretty interesting because it gives you a lot of insight into these various LLMs' NLP capabilities.
A few interesting stats were that I rated Gemini 4 Argon at 1775, GPT-6.1 Sol at 1744, GPT-6 Astra at 1723, Claude Fable 5.1 at 1623, and Claude Opus 5.5 at 1592. You'll find a few interesting things there, like how, although newer, more expensive models tend to perform better, some rare exceptions exist, like Kimi K2.5 slightly edging out Kimi K3.
Check out the site if you're interested in NLP and data science and want to see what level of frontier LLMs you can beat!