whatmodel.sh / GLM-4-Plus (0111)

GLM-4-Plus (0111)

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GLM-4-Plus (0111) is a closed-weights language model from Zhipu AI (Z.ai). Licence: proprietary.

Catalogue identity notes

Exact Arena entry 'glm-4-plus-0111' in the October 2026 pinned dataset. Comparison identity; no public run route inferred from leaderboard inclusion.

58.5±3.3comparison only: no current run option verifiedfrom 1 benchmark result across 1 source* thinly tested, treat the rank as provisional

$ how it compares

The LLMs ranked either side of GLM-4-Plus (0111), out of 1132 with a score, then more from Zhipu AI (Z.ai).

#modelscorewhereRAMreleased
320Qwen3 14B Alibaba59±1api $0.61/M +local~10GB2025-04
321Mercury 2 Inception59±2comparison only
322GLM-4-Plus (0111) Zhipu AI (Z.ai)59±3comparison only
323Jais 2 70B Chat Inception (G42)59±4comparison only2025-12
324DiffusionGemma 26B-A4B Google59±1comparison only2026-06
more from Zhipu AI (Z.ai)
654GLM-4 9B Chat Zhipu AI (Z.ai)47±2local~7.9GB2024-06

see all LLMs · find the ones that fit your machine

$ what it's good at

chat & writing▁▁▁▃▅▅▆█▆▆▆▂ #229 of 579 * · 95% of its score · 1 test

Beats MiniCPM5 2B, Granite 4.2 30B, Seed-OSS 36B Instruct here, though they rank higher overall. Trails LFM2.5 1.2B Instruct, LFM2.5 1.2B Thinking, LFM2.5 8B-A1B here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
LMArena (text)1342.7 ✎▁▁▁▂▃▃▃▆▆▇█▃ beats 180/379avg 1268▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 95%blunt

$ where to run it

No verified API or download recorded yet · add one

$ how the score was worked out · LMArena leaderboard dataset 95%

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works

sourceresultsshare of the scorelicence
LMArena leaderboard dataset1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 95%CC BY 4.0
prior · pull toward the middle▇ 5%
weighted average= 58.5

$ improve this page

Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit data on GitHub

Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.

data updated · sources and licences · json