Benchmark Almanac

Slide generation human evaluation (Z.ai)

GLM-5 67.5% Only in system cards

People compare HTML slide decks from two models on content, layout and visual quality. Metric is overall win rate.

In-house Z.ai evaluation. GLM-5 is compared with GLM-4.5.

Made by Zhipu AI (Z.ai) Released Feb 2026 Taste and style Tasks kept private Last in a system card Feb 2026 Last model added Feb 2026
Level
Everyday Most adults, without training
Scored
Graded by people Human experts grade or compare the outputs.
Answers
Open-ended Free-form text, documents, designs or media judged as a whole.
1
Model scored in lab cards
1
System card reports it, from 1 lab

GLM-5 leads with 67.5%

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

  1. 1 GLM-5 67.5%
#ModelScoreSettingDateSource
1 GLM-5 67.5% Feb 2026 Model card

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

Reported by the lab in its model card
0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) GLM-5 0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) GLM-5

Labs report it only in system cards

We read the headline results of 479 launch posts from 51 labs, and none of them list this benchmark. Some system cards do, below.

One system card reports it

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
17 Feb 2026 GLM-5 technical report 67.5 Slides human evaluation, overall win rate vs GLM-4.5 (Section 4.2, text) Capabilities

More in Writing and taste

All 24 in Writing and taste
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  • WritingBench Fading Models complete 1,000 real-world writing requests across 6 domains and 100 subdomains. A judge model scores each reply on five query-specific criteria. GPT-5 83.9
  • Creative Writing (MiniMax in-house) Only in system cards Models write creative pieces for real Hailuo AI user requests. Automatic assessments score the writing. MiniMax-Text-01 81.3%
  • DeepSeek Chinese functional writing evaluation Only in system cards Models answer 3,170 everyday Chinese writing prompts such as reports, emails and speeches. Pairwise judging against a baseline model gives a win rate. DeepSeek-V4-Pro 62.6%
  • Task-dependent output homogenization evaluation Only in system cards Models answer prompts several times. A judge scores functional diversity where it is wanted and consistency where one answer is right. Muse Spark 0.21
  • DeepSeek Chinese creative writing evaluation Only in system cards Models write Chinese fiction, prose, poetry and lyrics for 2,837 prompts. Pairwise judging gives separate win rates for instruction following and writing quality.