Zhipu (GLM) · open weights · writing benchmark
GLM-4.5 Air sits at #111 of 130 on ToneBench, toward the value end of the board, with a writing Elo of 847 and an overall score of 67.8 out of 100. We measured it by having it write all 9 of our real YouTube scripts, five times each, then scoring every draft blind against our own finished versions. Here is how it shook out.
Within Zhipu (GLM) it ranks 5th of 5. GLM-5 is the family's top writer here, about 936 Elo ahead, so this config trades some quality for whatever it saves you in cost or speed.
Among open-weights models, it comes in 31st of 47. Open weights still trail the closed frontier on pure voice fidelity, and you can see that in the gap at the top.
What it does best is Visual Cues: it ranks 95th on that dimension at 67.3, well below the board average. Its softer spot is Anti-Slop (69.2, 114th), which is the thing to watch if that metric matters most for your use.
It was uneven across the 9 scripts. Its best run was the product release announcement / personal observation (75.2) and its weakest was the personal technical walkthrough / agentic workflow case study (57.6), a spread of about 18 points. Worth knowing if your writing skews toward one of those formats.
On cost, it runs about $0.004/task. Gemini 2.5 Flash-Lite scores higher for less money, at $0.002/task, so on pure value this config is not the frontier. Still, it beats 3 models that cost noticeably more.
The shape is the story: the further a corner reaches, the stronger that dimension. Biggest edge over the board: Hook (-4.5); furthest behind: Length Discipline (-20.6).
Nine writing dimensions, each scored 0–100 and blended by the editorial weight shown. Rank is against all 130 current-ranked models. The thick bar is this model; the thin lines above and below are the current field's best model (darker) and average (lighter) on the same scale. The small ± number is its run-to-run variation.
The same 9 real scripts every current-ranked model writes, scored individually. Different formats stress different skills.
Every cell on this page is the mean of 5 independent runs per script; the ± numbers are the run-to-run standard deviation. Overall, GLM-4.5 Air varies by ± 5.6 points between runs versus a board median of ± 3.8, so it is swingier than the typical model here, worth knowing if you need repeatable output.
Its most volatile dimension is Anti-Slop (± 4.5 vs a board median of ± 2.6): two runs of the same brief can land visibly different anti-slop scores.
| Metric | This model | Board median | Verdict |
|---|---|---|---|
| Tone & Voice ? | 70.1 ± 2.8 | ± 2.2 | typical |
| Writing Craft ? | 71.7 ± 2.5 | ± 2.0 | typical |
| Substance & Value ? | 71.5 ± 3.4 | ± 2.6 | typical |
| Flow & Emotion ? | 65.5 ± 3.2 | ± 2.6 | typical |
| YouTube Structure ? | 65.5 ± 3.4 | ± 3.6 | typical |
| Hook ? | 75.8 ± 4.0 | ± 3.0 | typical |
| Length Discipline ? | 46.6 ± 8.7 | ± 8.6 | typical |
| Anti-Slop ? | 69.2 ± 4.5 | ± 2.6 | swingier than most |
| Visual Cues ? | 67.3 ± 7.3 | ± 4.7 | swingier than most |
Numbers we log on every run and rarely talk about. None of these affect the writing scores; cost and latency are informational.
The published overall of 67.8 is the consensus of three family-disjoint judges scoring the same 45 stored drafts blind with the identical rubric. The highest and lowest judge differ by 12.1 points on its overall. A typical amount of judge disagreement for this board. How the panel works: methodology.
z-ai/glm-4.5-air (provider default reasoning)z-ai/glm-4.5-air for automated_video_workflow (Task-7 exact OpenRouter endpoint pin novita/bf16)On ToneBench it ranks #111 of 130 with a writing Elo of 847 and an overall score of 67.8/100. That score comes from writing our 9 real YouTube scripts five times each and scoring every draft blind against our own finished versions across nine writing dimensions.
Not quite. Within Zhipu (GLM) it ranks 5th of 5; GLM-5 is the family's best writer here.
It costs about $0.004/task. Gemini 2.5 Flash-Lite scores higher for less, so it is not the value pick.
Its strongest dimension is Visual Cues (95th on the board, 67.3). Its weakest is Anti-Slop (114th on the board, 69.2). The full nine-metric breakdown is on this page.
Yes. Its best of our 9 scripts was the product release announcement / personal observation (75.2) and its weakest was the personal technical walkthrough / agentic workflow case study (57.6).
We run every script 5 times. GLM-4.5 Air's overall score varies by about ±5.6 points between runs, versus a board median of ±3.8. That is swingier than typical, so expect more draft-to-draft variation. The full per-metric variability table is on this page.
Via OpenRouter using the exact model/route id z-ai/glm-4.5-air, run on 2026-07-29. 5 runs per script, provider-default sampling, no fine-tuning; every draft scored blind with a fixed rubric by a three-family judge panel. Full details in the 'How we ran it' section and the methodology.
Yes, it is an open-weights model. Among open-weights models it ranks 31st of 47 for writing.