Alibaba Cloud has jumped on the DeepSeek bandwagon, making the Chinese AI startup’s models available on its platform.
The company’s decision is similar to other tech giants’: offering DeepSeek’s open-source systems to its users.
In a WeChat post, Alibaba Cloud said that users can now use the LLM – from training to deployment and inference – without writing a line of code. The company says this setup simplifies AI model development, making it faster and more efficient for developers and enterprises.
Users can explore DeepSeek’s AI models in Alibaba Cloud’s PAI Model Gallery, a collection of open-source large language models. The models can be deployed to power applications from text generation to complex reasoning tasks. Among the available options are DeepSeek’s flagship models, DeepSeek-V3 and DeepSeek-R1, which are touted as having been developed at a fraction of the usual cost and computing power required by major AI firms. The gallery also includes smaller versions of these models, like DeepSeek-R1-Distill-Qwen-7B, which have been optimised for efficiency and size.
For those less familiar, LLMs serve as the backbone of generative AI tools like OpenAI’s ChatGPT. Open-source models give developers the flexibility to tweak, expand, and refine an AI’s capabilities. Meanwhile, model distillation is a technique used to train smaller models to replicate the performance of larger ones, using less power for inference so with lower computational costs – an approach that many companies now rely on to efficiently scale AI applications.
Alibaba Cloud’s decision to incorporate DeepSeek’s models comes shortly after the business introduced its own Qwen 2.5-Max model, which is a direct competitor to DeepSeek-V3. It’s part of a broader trend where major cloud providers are incorporating DeepSeek’s technology to enhance the range of their offerings. Huawei Cloud, for example, partnered with AI infrastructure start-up SiliconFlow to bring DeepSeek’s models to its Ascend platform during the Lunar New Year holiday. Huawei claims its platform allows the models to run as smoothly as they do on premium global GPUs.
Tencent is also on board, supporting DeepSeek’s R1 model on its cloud computing platform, where users can get up and running with just a three-minute setup. Meanwhile, Nvidia has added DeepSeek-R1 to its NIM microservice, advertising the model’s advanced reasoning capabilities and efficiency in tasks like logical inference, maths, coding, and language understanding.
Other tech giants are making similar moves. Microsoft, a key investor in OpenAI, recently introduced R1 support on its Azure cloud and GitHub platforms, allowing developers to build AI applications that run locally on Copilot+ PCs. Amazon followed suit for its AWS customers.
Despite growing support for DeepSeek, some experts are sceptical about whether the models’ cost-saving breakthroughs are as significant as they are claimed. Fudan University computer science professor Zheng Xiaoqing pointed out that the reported cost savings for training DeepSeek-V3 did not account for earlier research and development expenses. In an interview with the Chinese newspaper National Business Daily, he argued that DeepSeek’s success stems from engineering optimisations rather than revolutionary innovation. As a result, he does not expect it to have a significant impact on AI chip demand or distribution.
For now, major cloud providers are keen to provide their users with access to these cost-effective AI models. Whether DeepSeek’s technology will have a further lasting impact on the AI landscape remains to be seen.
(Photo by Unsplash)
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