REPOGEO REPORT · LITE
wgwang/awesome-LLMs-In-China
Default branch main · commit f2a1119c · scanned 6/20/2026, 11:19:27 AM
GitHub: 6,452 stars · 561 forks
Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.
2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface wgwang/awesome-LLMs-In-China, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Explicitly state the repository is an 'Awesome List' in the README's opening.
Why:
CURRENT中国大模型大全,全面收集有明确来源的大模型情况,包括机构、来源信息和分类等,随时更新。
COPY-PASTE FIX中国大模型大全,一个**精选列表 (Awesome List)**,全面收集有明确来源的大模型情况,包括机构、来源信息和分类等,随时更新。
- hightopics#2Add relevant topics to the repository.
Why:
COPY-PASTE FIXlarge-language-models, llms, china, chinese-llms, awesome-list, ai, artificial-intelligence, nlp, deep-learning, foundation-models
- mediumhomepage#3Set the repository's homepage URL to itself.
Why:
COPY-PASTE FIXhttps://github.com/wgwang/awesome-LLMs-In-China
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- Pangu-α · recommended 2×
- Hugging Face Models · recommended 1×
- Baidu · recommended 1×
- Alibaba · recommended 1×
- Tencent · recommended 1×
- CATEGORY QUERYWhere can I find a comprehensive list of large language models developed in China?you: not recommendedAI recommended (in order):
- Hugging Face Models
- Baidu
- Alibaba
- Tencent
- SenseTime
- Zhipu AI
- 01.AI
- DeepSeek
- Huawei
- iFLYTEK
- ByteDance
- Baichuan
- Qwen
- InternLM
- DeepSeek-LLM
- ZhipuChat
- Yi
- Pangu-α
- Baidu AI Open Platform
- Alibaba Cloud AI
- Tencent Cloud AI
- Huawei Cloud AI
- arXiv
- 36Kr
- TMTPost
- Sina Tech
- TechNode
- South China Morning Post tech section
- The Information
- GitHub Repositories
AI recommended 30 alternatives but never named wgwang/awesome-LLMs-In-China. This is the gap to close.
Show full AI answer
- CATEGORY QUERYSeeking an overview of major AI large language models originating from Chinese institutions.you: not recommendedAI recommended (in order):
- ERNIE Bot
- SenseChat
- Tongyi Qianwen
- Zhipu AI's GLM Series
- Pangu-α
- iFlytek Spark
AI recommended 6 alternatives but never named wgwang/awesome-LLMs-In-China. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of wgwang/awesome-LLMs-In-China?passAI did not name wgwang/awesome-LLMs-In-China — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts wgwang/awesome-LLMs-In-China in production, what risks or prerequisites should they evaluate first?passAI did not name wgwang/awesome-LLMs-In-China — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo wgwang/awesome-LLMs-In-China solve, and who is the primary audience?passAI did not name wgwang/awesome-LLMs-In-China — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
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wgwang/awesome-LLMs-In-China — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite