# Yang Su (slim)

> Yang Su is agent research lead at Qwen series. Qwen3.5-0.8B, Qwen3.5-2B, Qwen3.6-27B and Qwen3.8-27B on Anchor Terminal, with grades, an about and public profiles.

- Full: https://www.anchorterminal.com/people/yang-su/index.md (~1,200 tokens) · this version ~980 tokens · JSON https://www.anchorterminal.com/people/yang-su/index.json · canonical https://www.anchorterminal.com/people/yang-su/
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-10-27
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Agent research lead, Qwen series.

- LinkedIn: https://www.linkedin.com/in/yang-su2000
- X: https://x.com/YangSu2000

## What Yang builds

- [Qwen3.5-0.8B](https://www.anchorterminal.com/tools/qwen3-5-0-8b.md), graded D, 46.7/100, in Open-weight models. Qwen3.5-0.8B is the smallest model in Alibaba's Qwen3.5 family, 0.8B language parameters with a vision encoder, thinking off by default and a 262,144-token context, published on Hugging Face in BF16 under Apache 2.0 for prototyping, fine-tuning and research. Agent research lead, Qwen series, researched 2026-10-27.
- [Qwen3.5-2B](https://www.anchorterminal.com/tools/qwen3-5-2b.md), graded D, 50.5/100, in Open-weight models. Qwen3.5-2B is a small model in Alibaba's Qwen3.5 family, 2B language parameters with a vision encoder, thinking off by default and a 262,144-token context, published on Hugging Face in BF16 under Apache 2.0 for prototyping, fine-tuning and research. Agent research lead, Qwen series, researched 2026-10-27.
- [Qwen3.6-27B](https://www.anchorterminal.com/tools/qwen3-6-27b.md), graded B, 67.2/100, in Open-weight models. Qwen3.6-27B is Alibaba's open-weight dense vision-language model of 27B parameters, tuned for agentic coding, with thinking on by default, preserved thinking across turns and a 262,144-token context, published on Hugging Face in BF16 and FP8 under Apache 2.0. Agent research lead, Qwen series, researched 2026-10-27.
- [Qwen3.8-27B](https://www.anchorterminal.com/tools/qwen3-8-27b.md), graded B, 68.6/100, in Open-weight models. Qwen3.8-27B is Alibaba's open-weight dense vision-language model of 27B parameters, with thinking on by default and a 262,144-token context, published on Hugging Face in BF16 and FP8 under Apache 2.0. Agent research lead, Qwen series, researched 2026-10-27.

## Works with

- [Eddie Wu](https://www.anchorterminal.com/people/eddie-wu/), Co-founder, Director and CEO, Alibaba Group
- [Jack Ma](https://www.anchorterminal.com/people/jack-ma/), Co-founder, Alibaba Group
- [Jane Jiang](https://www.anchorterminal.com/people/jane-jiang-2/), Co-founder and Chief People Officer, Alibaba Group
- [Jin Xu](https://www.anchorterminal.com/people/jin-xu/), First author, Qwen3-Omni Technical Report
- [Joe Tsai](https://www.anchorterminal.com/people/joe-tsai/), Co-founder and Chairman, Alibaba Group

## Questions

### Who is Yang Su?

Yang Su is agent research lead at Qwen series.

### What does Alibaba (Qwen team) make?

Anchor Terminal lists Qwen3.5-0.8B, Qwen3.5-2B, Qwen3.6-27B and Qwen3.8-27B from Alibaba (Qwen team).

### How are Yang's tools graded?

Qwen3.5-0.8B is graded D, 46.7 out of 100; Qwen3.5-2B is graded D, 50.5 out of 100; Qwen3.6-27B is graded B, 67.2 out of 100; Qwen3.8-27B is graded B, 68.6 out of 100, on Anchor Terminal's benchmark, which scores every listing against the same checklist.

## Sources

- https://www.linkedin.com/in/yang-su2000
- https://huggingface.co/Qwen/Qwen3.5-0.8B
- https://qwen.ai/blog?id=qwen3.5
- https://x.com/YangSu2000
- https://x.com/Alibaba_Qwen
- https://www.linkedin.com/company/alibaba-cloud-computing-company/
- https://qwen.ai/
- https://github.com/QwenLM/Qwen3.5
- https://huggingface.co/Qwen/Qwen3.5-2B
- https://qwen.ai/blog?id=qwen3.6-27b
- https://github.com/QwenLM
- https://huggingface.co/Qwen
- https://huggingface.co/Qwen/Qwen3.8-27B
- https://github.com/QwenLM/Qwen3.8

These are the people building the tools we list, named for their public role in the company or project behind a listing, from public pages, with the date it was researched.