Frontier Labs

DeepSeek posted about 150 openings on 8 September and not one of them is a research role, per a WeChat notice read closely by QbitAI and republished by 36Kr. They split into server-side development engineers across six directions, which are the large-model research platform, Agent framework components, R&D efficiency infrastructure, the DeepSeek API, online serving and data engineering, and agent elastic-compute engineers across two, platform development and low-level systems, with a target profile of senior backend people two to ten years in. QbitAI puts the whole company at 300 to 500 people, so a single round is worth somewhere between a quarter and a half of existing headcount, hired into one function; an investor at a front-line firm told Sina Tech the goal for this year is 1,000 people, which would put DeepSeek level with Zhipu, whose 2025 prospectus listed 883 employees. What the 150 are being hired to build has a name: DSec, for DeepSeek Elastic Compute, disclosed for the first time in the V4 technical report as three Rust components, an API gateway called Apiserver, an Edge agent on every host machine and a cluster monitor called Watcher, wired over a homemade RPC protocol on top of 3FS, the distributed filesystem DeepSeek open-sourced last year. Cui Tianyi, who runs the DeepSeek Harness team, gave the reason in one sentence: scale produces complexity, and the complexity turns around and demands more scale. Underneath it is the money. Reuters reported on 9 September that DeepSeek has hired CITIC Securities to prepare a listing on Shanghai’s STAR Market and aims to start the process this year, which TechNode carried the same morning; Sina’s wire adds that CITIC has made contact and entered due diligence, that the two sides have not signed a formal listing-tutoring agreement, and that DeepSeek has said nothing officially.

Z.AI, the entity Zhipu lists under in Hong Kong at stock code 2513, filed interim results on 31 August 2026 covering the six months to 30 June. Revenue was 953.892 million yuan, up 399.7 percent, while gross margin fell from 50.0 percent to 26.4 percent. The move is mix rather than discounting: open-platform and API revenue was 825.176 million yuan, up 2,735.7 percent, and went from 15.2 percent of revenue to 86.5 percent, while on-premises deployment fell from 73.7 percent of 2025 revenue to 13.5 percent of this half. Token volume on the MaaS platform is up more than 40 times since the start of 2026 and the average API selling price rose about 101 percent over the same stretch, so volumes surged while prices went up. That leaves the 24.6 percent gross margin on the open-platform and API business a cost problem, not a pricing one.

Harvey, the OpenAI-backed legal AI company, published its first post-trained model on 20 August. Harvey Tenet is a Kimi K3 base, post-trained with a rank-64 LoRA over the full network on a dataset of about 1,750 tasks. It completes almost twice as many held-out tasks on the Legal Agent Benchmark as base Kimi K3, and places second on that benchmark overall. Harvey ran ablations on candidate judge models against heavier frontier models and settled on Kimi 2.6 as the grader. Its M&A diligence work uses a GLM-5.2 orchestrator, taking rubric criteria pass rate from a 43.8 percent best baseline to 60.1 percent after self-distillation post-training.

Chinese cloud vendors are reselling competitors’ models at roughly 30 percent of list price, below their own cost, because in AI coding the customer names the model. Leiphone reported the discount ladder on 21 August from named cloud sales sources: 60 to 80 percent of list six months ago, 48 percent now common, roughly 30 percent at the low end. The same day, Approaching.AI vice-president Guan Jiawei told the South China Morning Post that domestic chips can only serve the low-quality inference tier, the one with weak demand and weak monetisation, and that high-quality tokens, especially coding, still depend on Nvidia. iFlytek said the same week that a flagship model trained entirely on domestic compute would reach the domestic first tier on code capability.

DeepSeek open-sourced Harness, an MIT-licensed agent framework, on 13 August. Within four days its repository had passed both anthropics/claude-code and openai/codex on GitHub stars, 148,734 against 141,759 and 106,470, while Anthropic’s repository carries no open-source license at all. The caveats are in the same API response: Harness is a pre-1.0 release candidate with its public issue tracker switched off, and stars measure attention rather than use.

DeepSeek raised API prices by up to 12x, 83 days after calling its 75 percent V4-Pro discount permanent. Tencent Cloud matched the move rather than undercutting it, and the repricing ran industry-wide: Zhipu has raised prices three times this year and Kimi K3 output passed 100 yuan per million tokens. The stretch of the market where Chinese models competed purely on price is closing.

DeepSeek finished shipping V4, and its day-0 domestic-chip support runs on Huawei Ascend (via Huawei’s CANN, its answer to Nvidia’s CUDA), Cambricon and Hygon. After the launch Alibaba, ByteDance and Tencent ordered hundreds of thousands of Ascend 950 processors.

An IDC survey found 47 percent of large US firms now run a Chinese model in at least one use case, and at one point mid-July all five top models on OpenRouter were Chinese. Coinbase, DoorDash, Airbnb and Cursor are named adopters, switching to cut the bill as UBS puts Chinese API prices at 10 to 20 percent of the US alternative.

DeepSeek open-sourced V4 under MIT with Huawei Ascend as a primary deployment path: 1.6 trillion parameters, million-token context, coding a hair behind the best Western models. The first sovereign stack.

DeepSeek closed its first outside round, roughly 7.4 billion dollars at a 50-billion-plus valuation. The founder wrote the biggest check; the only investor with a vote is a state fund.

A teardown found part of DeepSeek V4’s architecture was co-designed for Huawei’s Ascend 950DT inference chip. The model and the silicon are now being built for each other.

US Commerce ordered a leading AI lab to cut its two most capable models off from all foreign nationals worldwide, then reversed it a week later. Export controls reached model access, and retreated.