GoogleGemini 3.6 FlashVSZ.ai (Zhipu AI)GLM-5.2

Analysis by:the whichllmmodel Editorial Team|Updated: June 2026

Our Take

Both models perform almost identically, with an average score gap of just 2.6%. We recommend choosing GLM-5.2 as it is the more cost-effective option (being 1.4x cheaper) without sacrificing any real-world capability.

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Model Specs

Gemini 3.6 Flash

Website

Benchmarks & Scores

Coding (swe-bench-pro)

58.7%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)Winner (+1.8%)

93%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)

$3.00Input: $1.50 | Output: $7.50

Context Window

1.05M tokens

Model Specs

GLM-5.2

Open SourceAPI Available

Website 🤗HF

Benchmarks & Scores

Coding (swe-bench-pro)Winner (+3.4%)

62.1%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)

91.2%

graduate-level science QA

Cost & Context

Cost (per 1M tokens)1.4x cheaper

$2.15Input: $1.40 | Output: $4.40

Context Window

1.05M tokens

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Frequently Asked Questions about Gemini 3.6 Flash vs GLM-5.2

GLM-5.2 is cheaper than Gemini 3.6 Flash. GLM-5.2 has a blended cost of $2.15/1M tokens, which is about 1.4x cheaper than Gemini 3.6 Flash at $3.00/1M tokens.

GLM-5.2 is better for coding tasks on this benchmark. It scores 62.1% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases) compared to Gemini 3.6 Flash which scores 58.7%.

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