Chinese AI models have emerged as global leaders in 2026, with DeepSeek, Qwen, Kimi, and Doubao rivaling Western counterparts in capability. For researchers and professionals who use these platforms, Notebook Toolkit provides the bridge to save your conversations and research to NotebookLM.
Why Chinese AI Models Matter for Research
DeepSeek: has become one of the most capable models for coding, mathematics, and technical reasoning. Its R1 model introduced extended chain-of-thought reasoning that produces remarkably detailed problem-solving outputs.
Qwen (Tongyi Qianwen): by Alibaba offers strong multilingual capabilities with particular strength in Chinese-English bilingual tasks.
Kimi: by Moonshot AI pioneered the ultra-long context window, supporting conversations that span hundreds of thousands of tokens — ideal for analyzing entire books or lengthy reports.
Doubao: by ByteDance provides a versatile, user-friendly AI assistant with strong Chinese language understanding.
Setting Up Notebook Toolkit for Chinese AI Platforms
Getting started is straightforward:
- 1Install the Notebook Toolkit extension from the Chrome Web Store
- 2Sign in to your Notebook Toolkit account
- 3Navigate to any supported Chinese AI platform — Notebook Toolkit automatically detects them
Notebook Toolkit has a built-in capture button for Kimi (kimi.com). For DeepSeek (chat.deepseek.com), Qwen (tongyi.aliyun.com), and Doubao (doubao.com), capture the conversation page with the toolbar button or Alt+Shift+S — the same way you save any other website.
Capturing Chinese-Language Content
Notebook Toolkit handles Chinese text natively. When you capture a conversation in Chinese, every character is preserved perfectly. Mixed Chinese-English conversations are captured with both languages intact.
Multilingual Research in NotebookLM
Cross-model comparison: Save the same question answered by DeepSeek, ChatGPT, and Claude. Ask NotebookLM to compare their approaches.
Bilingual research: Save Chinese-language sources alongside English ones. NotebookLM can work with both languages.
Technical research: DeepSeek's detailed technical reasoning, combined with Claude's nuanced analysis, creates a more complete picture than any single model provides.
Best Practices
Tag your sources by AI model so you can filter them in NotebookLM. For bilingual research projects, consider creating separate NotebookLM notebooks for Chinese-primary and English-primary sources, then combine the most relevant sources from both for final synthesis.