Compare Claude 3.7 Thinking Sonnet by Anthropic against Z.ai: GLM 5 by Zhipu AI, context windows of 200K vs 203K, tested across 46 shared challenges. Updated February 2026.
41 challenges
Tests an AI's ability to make educated estimates based on technical knowledge
The total number of FLOPs required to train GPT‑3 is approximately 3.15 × 10²³.
Step‑by‑step reasoning:
Model size: GPT‑3 has 175 billion (1.75 × 10¹¹) trainable parameters.
Training data: According to the paper abstract, the model was trained on 300 billion (3 × 10¹¹) tokens.
FLOPs per token for training a transformer:
Calculation:
Total FLOPs ≈ 6 × (1.75 × 10¹¹) × (3 × 10¹¹)
= 6 × 5.25 × 10²²
= 3.15 × 10²³.
Consistency check: The GPT‑3 paper reports a training compute of 3,640 PF‑days. Converting:
1 PF‑day = 10¹⁵ FLOP/s × 86400 s = 8.64 × 10¹⁹ FLOPs.
3,640 PF‑days = 3,640 × 8.64 × 10¹⁹ ≈ 3.14 × 10²³ FLOPs, matching the estimate.
Thus, the total FLOPs required to train GPT‑3 is about 3.15 × 10²³.
Tests an AI's ability to understand game rules and strategy
Tests an AI's ability to write in distinct character voices
Recreate an interactive, nostalgic Pokémon battle UI in a single HTML file.
