GoogleGemini 3.5 FlashVSZ.ai (Zhipu AI)GLM-5.2
Our Take
We recommend choosing GLM-5.2 as it delivers superior coding capability while matching the reasoning accuracy of Gemini 3.5 Flash at a 1.6x API cost saving. Choose GLM-5.2 for superior overall value and coding efficiency.
▶WHY?
Benchmark Calculations & Evidence:
Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. Gemini 3.5 Flash scored 55.1%, while GLM-5.2 scored 62.1%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Gemini 3.5 Flash scored 92.2%, while GLM-5.2 scored 91.2%.
Cost Efficiency: Gemini 3.5 Flash pricing ($1.5/M input, $9/M output) is 1.6x cheaper than GLM-5.2 ($1.4/M input, $4.4/M output).
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Benchmarks & Scores
Coding (swe-bench-pro)
55.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+1.0%)
92.2%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$3.38Input: $1.50 | Output: $9.00Context Window
1.05M tokensBenchmarks & Scores
Coding (swe-bench-pro)Winner (+7.0%)
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)1.6x cheaper
$2.15Input: $1.40 | Output: $4.40Context Window
1.05M tokensFrequently Asked Questions about Gemini 3.5 Flash vs GLM-5.2
GLM-5.2 is cheaper than Gemini 3.5 Flash. GLM-5.2 has a blended cost of $2.15/1M tokens, which is about 1.6x cheaper than Gemini 3.5 Flash at $3.38/1M 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 3.5 Flash which scores 55.1%.
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