jeinlee1991/chinese-llm-benchmark resource
非线智能 NoneLinear - ReLE评测：中文AI大模型能力评测（持续更新）：目前已囊括374个大模型，覆盖chatgpt、gpt-5.4、谷歌gemini-3.1-pro、Claude-4.6、文心ERNIE-X1.1、ERNIE-5.0、qwen3.6-max、qwen3.6-plus、百川、讯飞星火、商汤senseChat等商用模型， 以及step3.5-flash、kimi-k2.6、ernie4.5、MiniMax-M2.7、deepseek-v4、Qwen3.6、llama4、智谱GLM-5.1、MiMo-V2、LongCat、gemma4、mistral等开源大模型。不仅提供排行榜，也提供规模超200万的大模型缺陷库！方便广大社区研究分析、改进大模型。 observed · 2026-08-28
Health v2 · maintenance only
89/100
- Activity 99
- Release rhythm 80
- Longevity 84
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: 5.0
- age_days: 1186
- days_rel: 134
- days_push: 10
- n_releases_24m: 57
Adoption not part of the score
6401 stars · 261 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
ReLE (formerly CLiB) is a continuously updated Chinese-language LLM capability benchmark and leaderboard covering ~400 commercial and open-source models across 7 domains and ~300 fine-grained dimensions (education, healthcare, finance, legal, reasoning, language, agent/tool use). It also publishes a defect (badcase) database of over 2 million cases for community research and model improvement.
Use cases
- compare chinese llm leaderboard rankings
- evaluate which chinese large language model to choose
- find weaknesses and failure cases of llms
- benchmark llm performance in education or medical exams
- compare open-source vs commercial chinese models
- research llm hallucination and refusal cases
- evaluate agent and tool-calling ability of chinese models
When to choose
- you need up-to-date, live evaluations of Chinese-language LLMs
- you want domain-specific rankings (education, healthcare, finance, legal, reasoning)
- you need a large badcase/defect corpus for model analysis or improvement
- you are selecting between Chinese commercial and open-source models
When to avoid
- you need English-only or multilingual benchmarking
- you need a runnable evaluation harness for your own private test sets rather than published rankings
- you require a formally licensed, reproducible academic benchmark (no license specified)
Facets
dataset · maturity active
benchmarking llm-inference machine-learning data-science large-language-models artificial-intelligence education healthcare fintech legal python cross-platform llm-evaluation chinese-llm leaderboard benchmark badcase-database model-selection rele live-evaluation natural-language-processing web
3 sources
- readme: https://github.com/jeinlee1991/chinese-llm-benchmark · fetched 2026-08-28 · 71233a1b7aec
- homepage: https://nonelinear.com · fetched 2026-08-29 · d57863145cbe
- site_page: https://nonelinear.com/static/about.html · fetched 2026-08-29 · 70d21e29ca2d
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| jeinlee1991/chinese-llm-benchmark | main | 89 |
For agents
markdown · JSON · MCP: product_card(name="jeinlee1991/chinese-llm-benchmark")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem