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On November 3, 2026, according to a report by Star Market Daily, multiple industry chain sources said that DeepSeek's next-generation large model, DeepSeek V5, plans to conduct pretraining based on Huawei Ascend chips; previously, Ascend chips were mainly used for inference tasks of DeepSeek large models. A same-day report by East Money mentioned that after the release of DeepSeek-V4 in April 2026, Huawei said that its full series of Ascend supernode products could fully support the V4 series models; on September 30, DeepSeek open-sourced infrastructure components for the Ascend computing platform, covering the TileLang compilation tool, DeepGEMM, FlashMLA, DeepEP, and others. The report also said that domestic computing power deployment is currently still concentrated on the inference side, and that the full-parameter post-training of DeepSeek-V4-Pro previously completed on the Ascend 910C cluster did not involve basic pretraining.
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Semiconductor Industry Review
Report: DeepSeek's Next-Generation Large Model V5 Plans to Use Ascend Chips for Pretraining
Reports suggest that DeepSeek's next-generation large model V5 will be pretrained on Huawei Ascend chips; previously, Ascend was mainly used for inference tasks on DeepSeek models. On September 30, DeepSeek open-sourced the TileLang compilation tool for the Ascend platform, computing libraries such as DeepGEMM, and the DeepEP communication library, corresponding one-to-one with NVIDIA platform components. The article also mentions that teams including Shenzhen Hetao College completed full-parameter post-training of the 1.6-trillion-parameter DeepSeek-V4-Pro on an Ascend 910C cluster, but this did not involve foundational pretraining.
East MoneySelected
DeepSeek V5 plans to pretrain on Ascend chips
According to sources in the industry chain, DeepSeek's next-generation large model, DeepSeek V5, plans to conduct pretraining based on Huawei Ascend chips; previously, Ascend was mainly used for inference tasks of DeepSeek models. The report mentions that after the release of DeepSeek-V4 in April 2026, Huawei stated that the full range of Ascend supernode products could fully support the V4 series models; on September 30, DeepSeek open-sourced infrastructure components for the Ascend computing platform, covering TileLang compilation tools, DeepGEMM, FlashMLA, DeepEP, and others. Currently, the implementation of domestic computing power remains concentrated on the inference side; the full-parameter post-training of DeepSeek-V4-Pro previously completed on the Ascend 910C cluster did not involve foundational pretraining.
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Phoenix Technology
Report: DeepSeek V5 Plans to Use Huawei Ascend Chips for Pretraining
According to a report by the STAR Market Daily, multiple industry chain sources say that DeepSeek's next-generation large model, DeepSeek V5, plans to conduct pretraining based on Huawei Ascend chips. Previously, Ascend chips were mainly used for inference tasks of DeepSeek large models.
Cailian Press
DeepSeek V5 plans to conduct pre-training based on Huawei Ascend chips
According to multiple industry chain sources, DeepSeek's next-generation large model DeepSeek V5 plans to conduct pre-training based on Huawei Ascend chips; previously, Ascend was mainly used for inference tasks of DeepSeek models. The report outlined that around the Spring Festival of 2025, Ascend completed the large-scale deployment of DeepSeek-V3/R1 in Huawei Cloud's Gui'an Data Center; after the release of DeepSeek-V4 in April 2026, the full series of Ascend SuperNode products could already support the V4 series; and on September 30, DeepSeek also open-sourced infrastructure components such as TileLang, DeepGEMM, and DeepEP for the Ascend platform. The report also noted that the implementation of domestic computing power is currently still concentrated on the inference side, and the ecosystem migration cost on the training side is the variable that determines the market ceiling.
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