Z.AI: GLM 4.6
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Z.AI: GLM 4.6 vs Z.ai: GLM 5
Compare Z.AI: GLM 4.6 and Z.ai: GLM 5, both from Zhipu AI, context windows of 203K vs 203K, tested across 47 shared challenges. Updated February 2026.
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Z.AI: GLM 4.6vsZ.ai: GLM 5
42 challenges
Why Z.AI: GLM 4.6?
1.5x cheaper overall$0.40/M in · $1.75/M out
Why Z.ai: GLM 5?
Leads 1 of 1 benchmarks
Stronger on SWE-bench Verified77.8% vs 68.0%
4 months newerFeb 2026
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Z.AI: GLM 4.6Z.ai: GLM 5
12 / 42
Estimate Complexityreasoning
Tests an AI's ability to make educated estimates based on technical knowledge
Z.ai: GLM 5
The total number of FLOPs required to train GPT‑3 is approximately 3.15 × 10²³.
Step‑by‑step reasoning:
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Model size: GPT‑3 has 175 billion (1.75 × 10¹¹) trainable parameters.
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Training data: According to the paper abstract, the model was trained on 300 billion (3 × 10¹¹) tokens.
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FLOPs per token for training a transformer:
- Forward pass: each parameter is used in one multiply‑add operation → ~2 FLOPs per parameter → 2 N FLOPs per token.
- Backward pass (gradient computation): roughly twice the forward cost → ~4 N FLOPs per token.
- Total: ~6 N FLOPs per token.
This approximation is standard for large transformer models and neglects small overheads like attention quadratic terms (which add only ~1–2% for GPT‑3’s sequence length).
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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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2 / 42
AI Board Game Logicreasoning
Tests an AI's ability to understand game rules and strategy
Z.AI: GLM 4.6
No content available for this output.
Z.ai: GLM 5
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3 / 42
Logic Puzzlereasoning
Tests an AI's ability to solve a simple but potentially confusing logic puzzle
Z.AI: GLM 4.6
No content available for this output.
Z.ai: GLM 5
No content available for this output.
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4 / 42
Stochastic Consistency Testanalysis
Tests an AI's randomness and creativity
Z.AI: GLM 4.6
No content available for this output.
Z.ai: GLM 5
No content available for this output.
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5 / 42
SVG Layout Challengeimage generation
Tests an AI's ability to generate vector graphics
Z.AI: GLM 4.6
No content available for this output.
Z.ai: GLM 5
No content available for this output.
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6 / 42
Xbox Controller SVG Artimage generation
Tests an AI's ability to create detailed SVG illustrations of gaming hardware
Z.AI: GLM 4.6
No content available for this output.
Z.ai: GLM 5
No content available for this output.
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7 / 42
Generate a Stand-Up Routineconversation
Tests an AI's humor and creative writing ability
Z.AI: GLM 4.6
No content available for this output.
Z.ai: GLM 5
No content available for this output.
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8 / 42
Realistic AI Interviewconversation
Tests an AI's ability to simulate personalities and predict future trends
Z.AI: GLM 4.6
No content available for this output.
Z.ai: GLM 5
No content available for this output.
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9 / 42
Satirical Fake News Headlineconversation
Tests an AI's humor and understanding of current events
Z.AI: GLM 4.6
No content available for this output.
Z.ai: GLM 5
No content available for this output.
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10 / 42
Character Voice Testconversation
Tests an AI's ability to write in distinct character voices
Z.AI: GLM 4.6
No content available for this output.
Z.ai: GLM 5
No content available for this output.
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11 / 42
Pokémon Battle UI Recreationweb design
Recreate an interactive, nostalgic Pokémon battle UI in a single HTML file.
Z.AI: GLM 4.6
No content available for this output.
Z.ai: GLM 5
No content available for this output.
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12 / 42
Mario Level UI Recreationweb design
Recreate an interactive, classic Mario level in a single HTML file.
Z.AI: GLM 4.6
Z.ai: GLM 5
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12 of 42