GoogleGemini 3.1 ProVSZ.ai (Zhipu AI)GLM-5.2
Our Take
We recommend GLM-5.2 for a 2.1x API cost saving and superior coding capability, or Gemini 3.1 Pro if your workflow requires peak reasoning. While GLM-5.2 is more cost-effective, Gemini 3.1 Pro holds a clear reasoning advantage. Choose GLM-5.2 for code generation, or Gemini 3.1 Pro for complex logical reasoning.
▶WHY?
Benchmark Calculations & Evidence:
Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. Gemini 3.1 Pro scored 54.2%, while GLM-5.2 scored 62.1%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Gemini 3.1 Pro scored 94.3%, while GLM-5.2 scored 91.2%.
Cost Efficiency: Gemini 3.1 Pro pricing ($2/M input, $12/M output) is 2.1x cheaper than GLM-5.2 ($1.4/M input, $4.4/M output).
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Benchmarks & Scores
Coding (swe-bench-pro)
54.2%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+3.1%)
94.3%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$4.50Input: $2.00 | Output: $12.00Context Window
1.05M tokensBenchmarks & Scores
Coding (swe-bench-pro)Winner (+7.9%)
62.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
91.2%graduate-level science QA
Cost & Context
Cost (per 1M tokens)2.1x cheaper
$2.15Input: $1.40 | Output: $4.40Context Window
1.05M tokensFrequently Asked Questions about Gemini 3.1 Pro vs GLM-5.2
GLM-5.2 is cheaper than Gemini 3.1 Pro. GLM-5.2 has a blended cost of $2.15/1M tokens, which is about 2.1x cheaper than Gemini 3.1 Pro at $4.50/1M tokens.
GLM-5.2 is better for coding tasks on this benchmark. It scores 62.1% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning) compared to Gemini 3.1 Pro which scores 54.2%.
Related Matchups
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