Model Arena
Blind-guess which model answered, then see the real leaderboard.
The market sells hype and rankings as received wisdom; this makes the learner generate and score their own blind comparison first, so the leaderboard becomes something they've personally calibrated against, not just trusted.
What goes in, what comes out
Learner submits their own prompt and gets back anonymized responses labeled A/B/C/D from different model families; before any reveal, they guess which label is which model and rate the outputs, building a personal prediction history. On reveal, real identities plus live leaderboard data (Artificial-Analysis/LMArena-style Elo, price, context window) populate next to the learner's guess, and every hover on a jargon term (MoE, distillation, quantization) links to a one-line, sourced definition.
A learner-authored prompt, and the learner's blind guesses/ratings for each anonymized response.
A reveal screen mapping labels to real models, a running personal calibration score (e.g. 7/10 correctly identified), and live leaderboard stats per model with jargon tooltips.
Number of models in the blind round (2-6), model pool (closed + open-weight mix), and whether leaderboard data refreshes live or uses a cached daily snapshot.
Free top-of-funnel lead magnet (no signup needed for one round) and in-module lab for AIE-130 (elective, Model Literate badge).
Concepts click when you open the machinery.
Three labs are already live and free — the same hands-on style this playground brings to its module.