Someone on Reddit built a tool that lets you benchmark yourself against AI language models. Same tests, same scoring. You sit down, answer the questions, and find out what size model you approximate.

The post took off, mostly because the original poster was having an absolute blast in the comments, treating themselves like a product listing. Quantization options. Token pricing. VRAM requirements. The bit where someone asked if they’d fit on an 8GB graphics card and they replied that they’d had Coca-Cola and cheesecake before testing “for an extra pump” — that’s genuinely funny. The whole thread had the energy of someone who understood exactly what they’d made and leaned into it without overselling it.

I’ve been fascinated by a project that’s been making the rounds lately: BalatroBench, which essentially lets large language models play Balatro, that brilliant poker-inspired roguelike that took the gaming world by storm last year. The concept is simple but elegant — feed the LLM the game state as text, let it decide what to do, and watch it either triumph or faceplant spectacularly.

For those unfamiliar, Balatro is a poker-based roguelike where you build synergies between cards, jokers, and special effects to reach increasingly absurd score targets. It’s the kind of game that requires both strategic planning and tactical decision-making, which makes it a genuinely interesting test for AI reasoning capabilities.