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CaixinUpdated Oct 25 19:40

DeepSeek open-sources inference framework DeepInfer, compatible with NVIDIA GPUs and Huawei Ascend 950

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On October 20, DeepSeek announced the open-sourcing of its internal large-scale cloud service inference framework DeepInfer, aiming to improve model inference efficiency and reduce deployment costs, compatible with NVIDIA GPUs and Huawei Ascend 950 chips. The framework has been used in the online service of the DeepSeek V4.1 Flash model, with a single cluster processing an average of 155 trillion Tokens per day, and revenue of about 38 US dollars per GPU hour calculated at off-peak electricity prices. This issue of the GPT Weekly also mentions news such as Anthropic launching the personal AI assistant Claude Duet and MiniMax breaking its IPO price in the Hong Kong stock market.

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The original text provides DeepInfer's chip compatibility scope and online service data, which can be used to assess changes in the deployment cost of the inference framework.

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2026-10-23 17:29:27 Source: Caixin.com Author: Gu Zhaowei Responsible Editor: Qu Yunxu

October 23, 2026 17:29

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On October 20, DeepSeek announced the open-sourcing of its internal large-scale cloud service inference framework DeepInfer, aimed at improving model inference efficiency and reducing deployment costs. Image: IC photo

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DeepSeek open-sources DeepInfer inference framework

On October 20, DeepSeek announced the open-sourcing of its internal large-scale cloud service inference framework DeepInfer, aimed at improving model inference efficiency and reducing deployment costs. The framework is compatible with Nvidia GPUs and Huawei Ascend 950 chips. DeepSeek disclosed that the framework has been used for online services of the DeepSeek V4.1 Flash model, with a single cluster processing 155 trillion Tokens per day on average, and revenue of about $38 per GPU hour calculated at off-peak electricity prices.

Anthropic launches personal AI assistant Claude Duet

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Responsible Editor: Qu Yunxu | Layout Editor: Li Donghao Image Editor: Li Bojing

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