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GLM 5.2 Performance Benchmarks

1 report

1 website

1 discussion

Latest report

Overview

GLM-5.2 (max) is a leading model in intelligence with a score of 51 on the Artificial Analysis Intelligence Index. It offers a 1 million token context window, supports text input and output, is faster than average, but is considered expensive compared to other open weight models of similar size.

Summary from artificialanalysis.ai.

Reports

One report so far. Additional coverage will appear here when it is linked to this story.

  1. artificialanalysis.ai

    GLM 5.2 Performance Benchmarks

    Read report →

Community reactions

Each reaction summarizes sampled comments from the linked discussion.

Hacker News · artificialanalysis.ai

GLM 5.2 Performance Benchmarks ↗
Hacker News discussion ↗

Historical count: 5 · 5 saved in sample · Historical sample

Analysis ready

Read this discussion’s reaction

Based on 5 sampled comments from this thread. Analyzed 2026-06-17.

  • Praise: GLM 5.2 excels in the 'AA-Omniscience Non-Hallucination Rate', outperforming models like DeepSeek and GPT 5.5, which highlights its reliability in uncertain scenarios.
  • Praise: The model's performance improvements, being 30% faster than its predecessor, indicate significant advancements in efficiency that could enhance user experience.
  • Praise: Local models are becoming increasingly useful, suggesting a shift towards more accessible AI solutions that could democratize technology for a wider audience.
  • Concern: Concerns arise over the validity of the 'AA-Omniscience Non-Hallucination Rate' benchmark, as it seems to favor models that avoid complex reasoning, potentially misleading users about true performance.
  • Concern: Skepticism about the benchmarks is prevalent, especially when models like Muse Spark are rated higher than GPT-5.5, raising doubts about the accuracy of the evaluations.
  • Concern: The high costs associated with deploying these models on local hardware may hinder accessibility, limiting their practical use for many developers and organizations.