SuperCLUE benchmark: Gemini-4-Argon scores highest, Kimi-K3.1-Pro leads Chinese models
Written by AI
Google’s Gemini-4-Argon and OpenAI’s GPT-6.1-Sol scored highest in the November benchmark by Chinese evaluator SuperCLUE. Moonshot AI’s Kimi-K3.1-Pro led the Chinese models, and SuperCLUE places it first in its own ranking.
Chinese evaluation group SuperCLUE published the November results of its general benchmark on 5 November. SuperCLUE evaluates Chinese-language large language models. This time it tested 19 Chinese and foreign models in five categories: agentic coding, mathematical and scientific reasoning, hallucination control, precise instruction following and long context.
Two different rankings
SuperCLUE orders the models by total score, but its numbered ranking leaves out foreign models and some Chinese ones. SuperCLUE shows these for reference only. That is why Gemini and GPT top the table without a rank number, while Kimi is ranked 1. SuperCLUE treats differences of less than one point as ties.
The table shows the eight highest-scoring models.
| Model | Developer | SuperCLUE classification | Rank | Total score |
|---|---|---|---|---|
| Gemini-4-Argon | closed source | – | 73.62 | |
| GPT-6.1-Sol | OpenAI | closed source | – | 71.76 |
| Kimi-K3.1-Pro | Moonshot AI | open source | 1 | 61.46 |
| DeepSeek-V4.1-Flash-1017 | DeepSeek | open source | 2 | 58.95 |
| GLM-5.3 | Zhipu AI | open source | 3 | 50.66 |
| Grok-4.7 | xAI | closed source | – | 49.66 |
| GLM-5.3-Flash | Zhipu AI | open source | 4 | 47.18 |
| Qwen3.8-Max-0902 | Alibaba | closed source | 5 | 43.22 |
Source: SuperCLUE general benchmark, November 2026. Figures are benchmark scores.
In an analysis published on Hugging Face, Korean company VIDRAFT points out that the scores are not error rates and that the total score should not be calculated as an average of the category scores. The ‘open source’ label is SuperCLUE’s own classification, not an independent licence assessment, VIDRAFT says, and results from a Chinese-language test should be checked against your own tasks.
Category leaders vary
GPT-6.1-Sol scored highest in coding (69.23) and reasoning (76.32). Gemini-4-Argon led in hallucination control (83.19) and long context (95.63). Both scored 68.97 in instruction following. A Kuai Keji news report, republished by AET, gives Gemini’s instruction-following score as 88.97, which differs from SuperCLUE’s table.
Among models classified as open source, DeepSeek-V4.1-Flash-1017 matched Gemini in coding (65.38). Kimi-K3.1-Pro scored higher than GPT in hallucination control (67.78 against 63.61). A single model’s results can vary widely: GLM-5.3 scored 77.60 in long context but 17.24 in instruction following.
VIDRAFT’s own Darwin-180B-RSI-R3, classified as open source, was also left out of the ranking. It came second in reasoning (73.68) but ninth on total score (43.08).
On the same day, Pandaily also reported on SuperCLUE’s October office agent benchmark, citing SuperCLUE’s website and an IT Home report. In the test, eight Chinese AI agents carried out Word, PowerPoint and Excel tasks. ByteDance’s Doubao Work scored 85.33, Moonshot AI’s Kimi Work 84.57 and Tencent’s WorkBuddy 83.99. Pandaily notes that the results come from a single organiser’s test environment and tasks.