evals.report
BenchmarksLabsCompareRun guidesIn the wild
Official benchmarks show reported scores. In-the-wild reports show what users hit after release: latency, cost, quota, regressions, surprising wins, and task-specific failures. These are source-linked anecdotes, not benchmark scores.
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GLM-5.2Z.ai

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Pranav Sriram · on GLM-5.2
X·@PranavSriram1·
Negative
For my research, Fable felt like a clear step change … I was excited about the GLM 5.2 hype and tried it; sadly it's nowhere close

Task Evaluating models for research work (alongside Fable and GPT-5.5 Pro).

anecdotal
@Hesamation · on GLM-5.2
X·@Hesamation·
Positive
GLM 5.2 ranks unusually high on FrontierSWE (long-horizon agentic engineering) … using it with OpenCode is also not far from the quality of Claude Code or Codex.

Task Day-to-day agentic coding with GLM-5.2 in OpenCode.

anecdotalhigh-signal user
Benchmark reproductionField testCodingAgents
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Guillermo Rauch · on GLM-5.2
X·@rauchg·
Positive
Genuinely impressed, almost shocked, at how good GLM-5.2 … is at coding. This changes things.
anecdotalhigh-signal user
Theo · on GLM-5.2
X·@theo·
Mixed
Having an open weight model surpass GPT-5.4 and every Gemini model is dope. That said - it's not cheap. Both Opus 4.8 and GPT-5.5 set to "medium" are cheaper and smarter than GLM-5.2
anecdotalhigh-signal user
Hassan · on GLM-5.2
X·@nutlope·
Positive
Asked GLM 5.2 (left) and Opus 4.8 (right) to design a menu and GLM has even better taste while being 4x cheaper. GLM also nailed a lot of small details like adding "chef's pick" and "vegetatian" tags to some dishes.

Task Asked GLM-5.2 and Opus 4.8 to design a restaurant menu (UI/design).

high-signal useroutput shown
Field testComparisonCostCodingMultimodal
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