Question 1

What is MMLU and why does it matter?

Accepted Answer

MMLU (Massive Multitask Language Understanding) tests a model's knowledge across 57 subjects including math, science, law, and humanities. A higher MMLU score indicates broader general knowledge. Frontier models score 90+, mid-tier 80-90, budget 65-80.

Question 2

Which AI model has the highest benchmark scores?

Accepted Answer

GPT-5.5 Pro and Claude Opus 4.8 consistently rank at the top across most benchmarks. GPT-5.5 leads on MATH (96.2) and Arena Elo (1380), while Claude Opus 4.8 excels at HumanEval (95.8). For budget models, DeepSeek V4 Pro offers the best benchmark-to-cost ratio.

Question 3

How do I use benchmark scores to choose a model?

Accepted Answer

Match benchmarks to your use case: MMLU for general knowledge tasks, HumanEval for code generation, MATH for mathematical reasoning, and Arena Elo for conversational quality. A model with 90+ MMLU and 90+ HumanEval handles most production tasks well. For budget-conscious choices, look for models scoring 85+ on your priority benchmark.

Question 4

Are benchmark scores the only factor in choosing a model?

Accepted Answer

No. Benchmark scores measure capability, but real-world performance also depends on API cost, context window size, rate limits, latency, and reliability. A model scoring 88 on MMLU at $0.15/1M tokens may be better value than one scoring 93 at $5.00/1M tokens. Use benchmarks alongside cost calculators for the full picture.

AI Model Benchmark Scores

MMLU Scores — All Models

Head-to-Head Benchmark Comparison

Understanding AI Model Benchmarks