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Mistral Large 3 vs GLM-4.7

A detailed comparison of Mistral Large 3 (Mistral) and GLM-4.7 (Zhipu AI) across pricing, performance, and features.

Pricing Comparison

MetricMistral Large 3GLM-4.7Difference
Input / 1M tokens$2.00$0.60-70%
Output / 1M tokens$5.00$2.20-56%
Context window128K200K
Max output16.384K128K

Benchmark Comparison

BenchmarkMistral Large 3GLM-4.7
MMLU-Pro83%84.3%
HumanEval91%
GPQA85.7%

Capabilities

CapabilityMistral Large 3GLM-4.7
code
reasoning
text
tool-use
vision

Mistral Large 3 Strengths

  • Low output cost ($5/1M) for a flagship
  • Strong multilingual support
  • European data sovereignty option

Mistral Large 3 Weaknesses

  • Lower benchmarks than top-tier competitors
  • Smaller ecosystem

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

Quick Verdict

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

Higher benchmarks: Mistral Large 3 scores higher on average across available benchmarks (87.0% avg).

Larger context: GLM-4.7 supports 200K tokens.

Choose GLM-4.7 if cost matters most. Choose Mistral Large 3 if you need the best possible quality for complex tasks.

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