Compare Gemini 2.5 Pro (I/O Edition) by Google AI against Z.ai: GLM 5 by Zhipu AI, tested across 34 shared challenges. Updated February 2026.
34 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.
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