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  "markdown": "Founder. Founder, DeepSeek. Founder and CEO, DeepSeek.\n\nLiang Wenfeng is founder and chief executive of DeepSeek. Through High-Flyer, the quantitative hedge fund he co-founded, he built the large-scale computing infrastructure that later supported AI research and led to DeepSeek's creation in 2023. He studied at Zhejiang University, where his master's research was in machine vision.\n\n## What Liang builds\n\n- [DeepSeek API](https://www.anchorterminal.com/tools/deepseek-api.md), graded E, 45.8/100, in Model APIs \u0026 inference. Hangzhou lab's API for the V4 model family, in the OpenAI Chat Completions, OpenAI Responses and Anthropic request formats, with off-peak pricing. Founder, researched 2026-10-27.\n- [DeepSeek Harness (dsh)](https://www.anchorterminal.com/tools/deepseek-harness.md), graded D, 49.5/100, in Agent harnesses. DeepSeek Harness (`dsh`) is DeepSeek's MIT-licensed agent harness, a developer preview built from plugins over the Cordis framework. It runs as a local Web UI, a one-shot headless command, an ACP server or a JSON-RPC server for its Python SDK. Founder, DeepSeek, researched 2026-10-27.\n- [DeepSeek Search and Fetch API](https://www.anchorterminal.com/tools/deepseek-search-api.md), graded D, 53.2/100, in Web search APIs. DeepSeek's Search and Fetch API gives agents live web results from DeepSeek's in-house search engine and single pages as Markdown, through two REST endpoints on an ordinary DeepSeek API key, billed per successful request. Founder and CEO, DeepSeek, researched 2026-10-27.\n- [DeepSeek-V3.2](https://www.anchorterminal.com/tools/deepseek-v3-2.md), graded C, 58.6/100, in Open-weight models. DeepSeek-V3.2 is DeepSeek's open-weight mixture-of-experts reasoning model with DeepSeek Sparse Attention, trained for tool use with a 128K-token context, published in FP8 under MIT. DeepSeek's API stopped serving it on 24 April 2026, moving to V4 Flash. Founder and CEO, DeepSeek, researched 2026-10-27.\n- [DeepSeek V4.1 Flash](https://www.anchorterminal.com/tools/deepseek-v4-1-flash.md), graded C, 59/100, in Open-weight models. DeepSeek V4.1 Flash is DeepSeek's open-weight multimodal mixture-of-experts model, 552B backbone parameters with 8B active in prefill and 16B in decode and a 1M-token context, published on Hugging Face under MIT. The 17 October update is graded. Founder and CEO, DeepSeek, researched 2026-10-27.\n- [DeepSeek-V4-Flash-0731](https://www.anchorterminal.com/tools/deepseek-v4-flash-0731.md), graded B, 62.4/100, in Open-weight models. DeepSeek-V4-Flash-0731 is the 31 July 2026 release of DeepSeek's V4 Flash, a mixture-of-experts text model with 284B parameters, 13B active and a 1M-token context, under MIT. DeepSeek's API retired V4 Flash on 10 September 2026. Founder and CEO, DeepSeek, researched 2026-10-27.\n\n## Works with\n\n- [Tianyi Cui](https://www.anchorterminal.com/people/tianyi-cui/), Cordis architecture paper coauthor; DeepSeek-AI\n- [Yifan Shi](https://www.anchorterminal.com/people/yifan-shi/), Cordis architecture paper first author; Peking University and DeepSeek-AI\n\n## Questions\n\n### Who is Liang Wenfeng?\n\nLiang Wenfeng is founder and chief executive of DeepSeek. Through High-Flyer, the quantitative hedge fund he co-founded, he built the large-scale computing infrastructure that later supported AI research and led to DeepSeek's creation in 2023. He studied at Zhejiang University, where his master's research was in machine vision.\n\n### What does DeepSeek make?\n\nAnchor Terminal lists DeepSeek API, DeepSeek Harness (dsh), DeepSeek Search and Fetch API, DeepSeek-V3.2, DeepSeek V4.1 Flash and DeepSeek-V4-Flash-0731 from DeepSeek. Hangzhou lab's API for the V4 model family, in the OpenAI Chat Completions, OpenAI Responses and Anthropic request formats, with off-peak pricing.\n\n### How are Liang's tools graded?\n\nDeepSeek API is graded E, 45.8 out of 100; DeepSeek Harness (dsh) is graded D, 49.5 out of 100; DeepSeek Search and Fetch API is graded D, 53.2 out of 100; DeepSeek-V3.2 is graded C, 58.6 out of 100; DeepSeek V4.1 Flash is graded C, 59 out of 100; DeepSeek-V4-Flash-0731 is graded B, 62.4 out of 100, on Anchor Terminal's benchmark, which scores every listing against the same checklist.\n\n## Sources\n\n- https://www.zju.edu.cn/english/2025/0313/c19573a3026836/page.htm\n- https://api-docs.deepseek.com\n- https://x.com/deepseek_ai\n- https://github.com/deepseek-ai/deepseek-harness\n- https://arxiv.org/abs/2608.25512\n- https://github.com/deepseek-ai\n- https://api-docs.deepseek.com/guides/search\n- https://www.deepseek.com/\n- https://en.wikipedia.org/wiki/Liang_Wenfeng\n- https://huggingface.co/deepseek-ai/DeepSeek-V3.2\n- https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017\n- https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731\n\nThese 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. They don't work for Anchor Terminal (our own team is on the about page, /about/#author). We show public roles, public profiles and what the listing pages show, nothing private. To correct something, send an about or a photo, or have a page removed, write to privacy@anchorterminal.com.\n",
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