Reasoning Evaluation - Interactive Visualization

Evaluating LLM reasoning requires benchmarks that resist simple pattern-matching. AIME tests mathematical olympiad problems (only 9% accuracy for GPT-4o without reasoning, 74% for o1). GPQA Diamond tests PhD-level science questions. Codeforces tests competitive programming. Pass@k measures the probability that at least one of k model samples is correct - a metric that rewards models which can reason, even if not perfectly reliably. Chain-of-thought consistently adds 5-10% accuracy across all benchmarks.

• Benchmark radar chart: visualize model strengths and weaknesses across 5 dimensions
• Pass@k curves: see how accuracy grows with k for each model
• Toggle CoT: see exactly how much chain-of-thought helps each model on each benchmark
• Model selector: compare GPT-4o, o1, Claude 3.5 Sonnet, DeepSeek-R1
• Bar charts for each benchmark with click-to-toggle model comparison
• k slider from 1 to 64: simulate the majority@k / best-of-n sampling regime

Part of the EngineersOfAI Interactive 3D - free interactive visualizations covering every major concept in machine learning and AI engineering. Hover any element for a plain-English explanation. No code required.