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GLM-4.7 vs Gemini 2.5 Pro

A detailed comparison of GLM-4.7 (Zhipu AI) and Gemini 2.5 Pro (Google) across pricing, performance, and features.

Pricing Comparison

MetricGLM-4.7Gemini 2.5 ProDifference
Input / 1M tokens$0.60$1.25+108%
Output / 1M tokens$2.20$10.00+355%
Context window200K1M
Max output128K65.536K

Benchmark Comparison

BenchmarkGLM-4.7Gemini 2.5 Pro
MMLU-Pro84.3%87.5%
HumanEval93.5%
GPQA85.7%76%

Capabilities

CapabilityGLM-4.7Gemini 2.5 Pro
audio
code
reasoning
text
tool-use
vision

GLM-4.7 Strengths

  • Excellent value — strong benchmarks at $0.60/$2.20
  • Open-weight (MIT license)
  • Top scores on AIME 25 and BrowseComp

GLM-4.7 Weaknesses

  • No tool-use support yet
  • 358B parameters — still heavy for self-hosting
  • Smaller ecosystem than OpenAI/Anthropic

Gemini 2.5 Pro Strengths

  • Competitive pricing for its capabilities
  • 1M context window
  • Well-tested and stable

Gemini 2.5 Pro Weaknesses

  • Being superseded by Gemini 3 Pro

Quick Verdict

Best value: GLM-4.7 is the more affordable option at $0.6/$2.2 per 1M tokens.

Higher benchmarks: Gemini 2.5 Pro scores higher on average across available benchmarks (85.7% avg).

Larger context: Gemini 2.5 Pro supports 1M tokens.

Choose GLM-4.7 if cost matters most. Choose Gemini 2.5 Pro if you need the best possible quality for complex tasks.

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