GoogleGemini 3.1 ProVSZ.ai (Zhipu AI)GLM-4.6
Our Take
We recommend Gemini 3.1 Pro if you need peak intelligence for complex complex codebases, multi-file repositories, and architectural planning, or the 4.5x cheaper GLM-4.6 if your workflow is limited to multi-file code and clearly defined tasks. While Gemini 3.1 Pro holds a major reasoning advantage, GLM-4.6 is optimized for high-volume budget pipelines. Choose Gemini 3.1 Pro for architectural codebase planning, or GLM-4.6 to maximize your budget for basic scripts.
▶WHY?
Benchmark Calculations & Evidence:
Coding Evaluation: Gemini 3.1 Pro was evaluated on SWE-bench Pro (scoring 54.2%), while GLM-4.6 was evaluated on SWE-bench Verified (scoring 68%).
Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. Gemini 3.1 Pro scored 94.3%, while GLM-4.6 scored 82.9%.
Cost Efficiency: GLM-4.6 pricing ($0.6/M input, $2.2/M output) is 4.5x cheaper than Gemini 3.1 Pro ($2/M input, $12/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 (+11.4%)
94.3%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$4.50Input: $2.00 | Output: $12.00Context WindowLarger
1.05M tokensBenchmarks & Scores
Coding (swe-bench-verified)
68%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)
82.9%graduate-level science QA
Cost & Context
Cost (per 1M tokens)4.5x cheaper
$1.00Input: $0.60 | Output: $2.20Context Window
202.75k tokensFrequently Asked Questions about Gemini 3.1 Pro vs GLM-4.6
GLM-4.6 is cheaper than Gemini 3.1 Pro. GLM-4.6 has a blended cost of $1.00/1M tokens, which is about 4.5x cheaper than Gemini 3.1 Pro at $4.50/1M tokens.
For coding tasks, Gemini 3.1 Pro scores 54.2% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning), while GLM-4.6 scores 68% on swe-bench-verified (multi-file code and clearly defined tasks).
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