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GLM-4.7 vs Llama 4 Maverick

A detailed comparison of GLM-4.7 (Zhipu AI) and Llama 4 Maverick (Meta) across pricing, performance, and features.

Pricing Comparison

MetricGLM-4.7Llama 4 MaverickDifference
Input / 1M tokens$0.60$0.31-48%
Output / 1M tokens$2.20$0.85-61%
Context window200K1M
Max output128K32K

Benchmark Comparison

BenchmarkGLM-4.7Llama 4 Maverick
MMLU-Pro84.3%80.5%
HumanEval90.2%
GPQA85.7%

Capabilities

CapabilityGLM-4.7Llama 4 Maverick
code
reasoning
text
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

Llama 4 Maverick Strengths

  • Open-source and self-hostable
  • 1M context window
  • Very competitive via API providers

Llama 4 Maverick Weaknesses

  • Requires significant compute to self-host
  • Fewer tool-use capabilities than proprietary models

Quick Verdict

Best value: Llama 4 Maverick is the more affordable option at $0.31/$0.85 per 1M tokens.

Higher benchmarks: Llama 4 Maverick scores higher on average across available benchmarks (85.3% avg).

Larger context: Llama 4 Maverick supports 1M tokens.

Choose Llama 4 Maverick if cost matters most. Choose GLM-4.7 if you need the best possible quality for complex tasks.

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