Alibaba Cloud (Qwen)Qwen3.7-MaxVSZ.ai (Zhipu AI)GLM-5.2
Our Take
We recommend GLM-5.2 for a 1.7x API cost saving at identical performance levels. While both models deliver similar intelligence, GLM-5.2 is the optimal choice for high-volume pipelines. Choose GLM-5.2 for budget efficiency without sacrificing quality.
▶WHY?
Benchmark Calculations & Evidence:
Performance Match: Both models perform almost identically, with an average score gap of just 1.4% across reasoning and coding benchmarks.
Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. Qwen3.7-Max scored 60.6%, while GLM-5.2 scored 62.1%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Qwen3.7-Max scored 92.4%, while GLM-5.2 scored 91.2%.
Cost Efficiency: GLM-5.2 pricing ($1.4/M input, $4.4/M output) is 1.7x cheaper than Qwen3.7-Max ($2.5/M input, $7.5/M output).
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Benchmarks & Scores
Coding (swe-bench-pro)
60.6%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+1.2%)
92.4%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$3.75Input: $2.50 | Output: $7.50Context Window
1.05M tokensBenchmarks & Scores
Coding (swe-bench-pro)Winner (+1.5%)
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)1.7x cheaper
$2.15Input: $1.40 | Output: $4.40Context Window
1.05M tokensFrequently Asked Questions about Qwen3.7-Max vs GLM-5.2
GLM-5.2 is cheaper than Qwen3.7-Max. GLM-5.2 has a blended cost of $2.15/1M tokens, which is about 1.7x cheaper than Qwen3.7-Max at $3.75/1M 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 Qwen3.7-Max which scores 60.6%.
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