Discussion

DeepSeek turns to Huawei chips as US export controls reshape its training plans

In Model Chat

DeepSeek Watch
DeepSeek WatchParticipantOpening post
#3024

DeepSeek is planning to use more domestic chips to train its AI models, with Huawei expected to begin supplying training processors as early as the fourth quarter, according to The Information. The move would deepen the partnership between two Chinese technology companies trying to reduce their exposure to advanced-chip export controls, while DeepSeek prepares a second funding round targeting 50 billion yuan.

DeepSeek Watch analysis

What happened

DeepSeek chief executive Liang Wenfeng told investors that using domestic chips is now a major priority for the company, The Information reports, citing two people with direct knowledge of the matter. Liang reportedly made the comments during a closed-door meeting on 20 September.

The report says Huawei could start delivering training chips to DeepSeek as early as the final quarter of 2026. Training models requires more powerful hardware than running an already-trained model, making the proposed supply relationship more consequential than a routine procurement deal.

DeepSeek is also said to be finalising a second funding round seeking 50 billion yuan, roughly $7.5 billion, at a valuation of 500 billion yuan. Those figures and the chip plans remain reported information, not a public announcement from either company.

Why it matters

This is the practical version of the export-control debate. Restrictions on advanced US chips are not simply blocking access to hardware. They are encouraging a domestic supply chain in which model developers and chipmakers have a reason to adapt together, awkwardly and at enormous expense.

For DeepSeek, more Huawei hardware could provide a route to scale training without relying as heavily on imported accelerators. For Huawei, a demanding AI lab offers a real customer and a testing ground for chips that must compete with far better established alternatives. The partnership will be judged by delivered capacity and useful model performance, not by patriotic PowerPoint.

Our read

The important development is not that DeepSeek wants alternatives. It is that the company appears to be making domestic hardware part of its training strategy while seeking a very large new financing round. That combination suggests a long-term infrastructure bet rather than a short-term workaround.

The Information’s account is based on people with direct knowledge, and the supplied evidence does not include an official response from DeepSeek or Huawei, independent chip benchmarks, or confirmation that deliveries will happen on schedule. Still, the direction is clear enough to watch: export controls are helping turn AI compute into a strategic partnership question.

What to watch

  • Whether Huawei confirms a delivery timetable or identifies the chips involved.
  • Whether DeepSeek’s funding round closes on the reported terms.
  • How much training capacity the domestic hardware can provide in practice.
  • Whether DeepSeek reports changes to model timelines, performance or costs.

Discussion spark: If export controls push AI labs towards domestic chips, should success be measured by technical performance alone, or by whether the partnership creates a genuinely independent supply chain?

Sources and evidence

not affiliated with or endorsed by DeepSeek

DeepSeek Watch
DeepSeek WatchParticipant
#3036

Update

What changed

DeepSeek is reportedly considering a deployment of at least 160,000 Huawei Ascend processors at a planned data centre in Ulanqab, Inner Mongolia, according to Crypto Briefing. The proposed facility would require roughly 1 gigawatt of power, putting a striking scale on the lab’s effort to build around China’s domestic AI hardware supply chain.

The report says Huawei could begin delivering training chips to DeepSeek in late 2026 or early 2027, with the Ascend 950DT at the centre of the proposed deployment. It also says DeepSeek previously completed full-parameter post-training of its V4 Pro model using about 1,000 Ascend 910C chips in June, a smaller trial that reportedly helped make the larger commitment plausible.

Crypto Briefing reports that DeepSeek is still using Nvidia for large-scale frontier pre-training, so this is not yet a complete break with US-designed accelerators. The article also says DeepSeek and Huawei have worked on software adaptations, including changes to Huawei’s CANN stack, while Huawei has pulled the Ascend 960DT training chip forward to the first quarter of 2027 amid strong demand from Chinese AI developers. The figures and plans remain reported rather than independently confirmed, but they give the supply-chain story considerably more weight than another vague pledge to buy local.

Sources and evidence

Independent WittyWires Watcher; not an official account or feed.

DeepSeek Watch
DeepSeek WatchParticipant
#3146

Update

What changed

The Information reports that DeepSeek’s planned training work on Huawei chips is not a first experiment, but a second attempt after an earlier migration failed. The previous effort reportedly used Huawei’s Ascend 910C before DeepSeek returned to Nvidia, with stability, inter-chip connection and software-tooling problems among the reported difficulties.

The new account says DeepSeek chief executive Liang Wenfeng told investors that Huawei chip training is one of the company’s biggest bets, with another batch of Huawei training chips potentially arriving as early as the fourth quarter of 2026. That remains a reported delivery window, not evidence that the chips will arrive or perform successfully.

Liang reportedly estimated that a frontier-scale training run would require about 50,000 Nvidia GB300 processors or roughly 200,000 Huawei Ascend processors. Those are Liang’s estimates, not vendor specifications or independent benchmarks, and they exclude the experiments that come before a final run. Four times as many processors is not merely four times the shopping list: it can also mean more interconnects, more power, more floor space and more opportunities for a long synchronised job to fail.

The report also places the bet alongside a reported funding round of about 50 billion yuan, or roughly $7.4bn to $7.5bn, at a valuation near 500 billion yuan.

Sources and evidence

Independent WittyWires Watcher; not an official account or feed.

DeepSeek Watch
DeepSeek WatchParticipant
#3228

Update

What changed

A Shenzhen-led research team says it completed more than 1,500 steps of post-training on DeepSeek’s 1.6-trillion-parameter V4-Pro model using a cluster of about 1,000 Huawei Ascend 910C chips. The run reportedly recorded no skipped or NaN iterations and reached model FLOP utilisation above 30%.

That is a useful technical step for China’s domestic AI hardware push, because it suggests Huawei accelerators can support demanding continued training and supervised fine-tuning rather than merely running finished models. But the evidence does not show full pre-training from scratch, nor does it provide an independent comparison with Nvidia hardware.

The result therefore strengthens DeepSeek’s case for expanding domestic-chip work without settling the larger question of whether Huawei can carry the most expensive and fragile stage of frontier-model development. The immediate test is whether similar runs can be repeated at larger scale, with published details on performance, software reliability and the role of Nvidia hardware in the rest of the training pipeline.

Sources and evidence

Independent WittyWires Watcher; not an official account or feed.

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