PeopleofSuperintelligence

Researcher

Zehui Ren

Zehui Ren is a member of the DeepSeek-AI team in Hangzhou, China, which develops open-source language models. In 2024, Ren coauthored papers on DeepSeek LLM, DeepSeek-V2, the Fire-Flyer AI-HPC architecture for a 10,000-GPU cluster, and the 671B-parameter Mixture-of-Experts model DeepSeek-V3. Their name is also on the reasoning model DeepSeek-R1, which appeared on arXiv in January 2025 and in Nature in September 2025. Later papers with Ren as an author included DeepSeek-V3.2 in December 2025 and the DeepSeek-V4 preview in April 2026, whose larger model has 1.6T parameters and a one-million-token context.

Now at
DeepSeek

Timeline

  1. January 2024

    DeepSeek LLM at 67B

    DeepSeek LLM appears in January 2024 with them among its authors. The project is dedicated to advancing open-source language models, and its 67B model surpasses LLaMA-2 70B on various benchmarks, particularly in code, mathematics and reasoning.

  2. May 2024

    The DeepSeek-V2 model

    They are among the authors of DeepSeek-V2, posted in May 2024. It is a Mixture-of-Experts language model with 236B total parameters, of which 21B are activated for each token, built on Multi-head Latent Attention and DeepSeekMoE.

  3. August 2024

    Fire-Flyer AI-HPC architecture

    In August 2024, Ren is among the authors of the Fire-Flyer AI-HPC paper on hardware-software co-design for deep learning. For deep learning training, the team deploys the Fire-Flyer 2 cluster with 10,000 PCIe A100 GPUs.

  4. December 2024

    DeepSeek-V3 with 671B parameters

    In December 2024, the DeepSeek-V3 Technical Report appears with them among its authors. DeepSeek-V3 is a Mixture-of-Experts model with 671B total parameters and 37B activated for each token, pre-trained on 14.8 trillion tokens.

  5. January 2025

    Reasoning with DeepSeek-R1

    The DeepSeek-R1 paper of January 2025 lists them among its authors. It shows that the reasoning abilities of large language models can be incentivized through pure reinforcement learning.

  6. September 2025

    DeepSeek-R1 in Nature

    Nature publishes the DeepSeek-R1 paper in September 2025, with authors from the DeepSeek-AI Team in Hangzhou, China, among them Zehui Ren.

  7. December 2025

    DeepSeek-V3.2 and sparse attention

    DeepSeek-V3.2 arrives in December 2025 with them among its authors. It introduces DeepSeek Sparse Attention and a scalable reinforcement learning framework, and its high-compute variant, DeepSeek-V3.2-Speciale, achieves gold-medal performance in the 2025 International Mathematical Olympiad and the International Olympiad in Informatics.

  8. April 2026

    The DeepSeek-V4 preview

    In April 2026, they are among the authors of the DeepSeek-V4 preview. It comprises DeepSeek-V4-Pro with 1.6T parameters and DeepSeek-V4-Flash with 284B parameters, both supporting a context length of one million tokens.

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes DeepSeek. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  2. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes DeepSeek. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.
  3. 5,000 frontier users would be 38.2% of the core labs' 13,100 reported staffIncludes DeepSeek. 5,000 frontier users would be 38.2% of the core labs' 13,100 reported staff. We test the estimate against 3,913 named model contributors and dated all-staff records across Google DeepMind, OpenAI and Anthropic, plus six additional frontier-grade labs.
  4. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes DeepSeek. We estimate that alumni of 17 major AI labs went on to found or lead 350 other organizations, including 226 they founded, and we trace 472 career moves directly between 23 labs since 2010.

Sources and credits

Photo: We have no published photo of Zehui Ren yet. Send us a free-licensed photo.

  1. DeepSeek LLM: Scaling Open-Source Language Models with Longtermism arxiv.org. Checked 22 October 2026.
  2. DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model arxiv.org. Checked 22 October 2026.
  3. Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning arxiv.org. Checked 22 October 2026.
  4. DeepSeek-V3 Technical Report arxiv.org. Checked 22 October 2026.
  5. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning arxiv.org. Checked 22 October 2026.
  6. DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning | Nature nature.com. Checked 22 October 2026.
  7. DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning (Nature, 2025) - IDEAS/RePEc ideas.repec.org. Checked 22 October 2026.
  8. DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models arxiv.org. Checked 22 October 2026.
  9. DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence arxiv.org. Checked 22 October 2026.