GoogleGemini 2.5 ProVSZ.ai (Zhipu AI)GLM-4.7
Our Take
We recommend choosing GLM-4.7 as it delivers superior coding capability while matching the reasoning accuracy of Gemini 2.5 Pro at a 3.4x API cost saving. Choose GLM-4.7 for superior overall value and coding efficiency.
▶WHY?
Benchmark Calculations & Evidence:
Coding Benchmarks: Both models were evaluated on the SWE-bench Verified benchmark. Gemini 2.5 Pro scored 59.6%, while GLM-4.7 scored 73.8%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Gemini 2.5 Pro scored 84.4%, while GLM-4.7 scored 85.7%.
Cost Efficiency: Gemini 2.5 Pro pricing ($1.25/M input, $10/M output) is 3.4x cheaper than GLM-4.7 ($0.6/M input, $2.2/M output).
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Benchmarks & Scores
Coding (swe-bench-verified)
59.6%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)
84.4%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$3.44Input: $1.25 | Output: $10.00Context WindowLarger
1.05M tokensBenchmarks & Scores
Coding (swe-bench-verified)Winner (+14.2%)
73.8%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)Winner (+1.3%)
85.7%graduate-level science QA
Cost & Context
Cost (per 1M tokens)3.4x cheaper
$1.00Input: $0.60 | Output: $2.20Context Window
202.75k tokensFrequently Asked Questions about Gemini 2.5 Pro vs GLM-4.7
GLM-4.7 is cheaper than Gemini 2.5 Pro. GLM-4.7 has a blended cost of $1.00/1M tokens, which is about 3.4x cheaper than Gemini 2.5 Pro at $3.44/1M tokens.
GLM-4.7 is better for coding tasks on this benchmark. It scores 73.8% on swe-bench-verified (multi-file code and clearly defined tasks) compared to Gemini 2.5 Pro which scores 59.6%.
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