The parameter race has reached a new magnitude—Tongyi Qianwen just dropped the trillion-parameter bomb named Qwen3-Max-Preview. Officially, it outperforms its predecessor Qwen3-235B in dialogue fluency, complex task handling, and instruction comprehension.


Interestingly, the comments section is flooded with two dominant voices: half demanding "When will it be open-source?" while the other half are already experimenting on platforms like AnyCoder. This divide perfectly mirrors the current state of the AI community—eager for cutting-edge breakthroughs yet committed to maintaining open-source ecosystems.

On technical specifics, the official release only mentions benchmark improvements over previous versions but avoids direct comparisons with GPT-5 Pro or Gemini 2.5 Pro. This selective disclosure recalls a netizen’s quip: "Trillion parameters are like the numbers on gym weight plates—what really matters is what you can lift with them."

Currently accessible through:

- [Qwen Chat](https://chat.qwen.ai)

- [Alibaba Cloud API](https://modelstudio.console.alibabacloud.com/?tab=doc#/doc/?type=model&url=2840914_2&modelId=qwen3-max-preview)

- [AnyCoder integration](https://huggingface.co/spaces/akhaliq/anycoder)

Notably, while the Tongyi Qianwen series is renowned for open-source contributions, the Max line has consistently remained proprietary. Faced with relentless queries like "Will it be open-source?", the official account has gone radio silent. This ambiguity may hint at a new balancing act between commercialization and open-source—after all, the electricity bill for training trillion-parameter models isn’t something idealism alone can cover.

(Note: All feature screenshots and performance data are from official sources; actual results may vary by use case.)