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DeepSeek’s March 2025 announcement covered five code repositories—not its entire AI development process. Experts welcomed the code release as useful to the community, while one argued it could unsettle competitors. That competitive effect is a possibility, not a measured result.
What did DeepSeek announce?
On 7 March 2025, ITPro reported that DeepSeek planned to open-source five code repositories. The company described them as “small but sincere progress with full transparency.” It said the repositories contained building blocks used in its online service and had been “documented, deployed, and battle-tested in production,” according to the post quoted by ITPro.
Cosine co-founder and CEO Alistair Pullen welcomed the move: “DeepSeek has gone a step further by open sourcing a lot of the code they use, which is awesome for the community.” Sharing production code can give developers material to inspect and potentially build on. The report, however, does not establish the repositories’ present contents, license status, or maintenance state.
How open is DeepSeek?
The announcement was a limited disclosure, not a release of every element behind DeepSeek’s AI. ITPro said the company had not open-sourced all of its code or key parts of model development such as training datasets. To understand what “open” means in this case, separate the components:
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- Source code: The announcement concerned five repositories of code used in the online service.
- Model weights: The report does not establish that the repository announcement disclosed model weights.
- Training data: ITPro said DeepSeek had not released its training datasets as part of the disclosure it covered.
- Training methods: The report does not describe the announcement as a release of DeepSeek’s full training methodology.
- Reuse terms: The report does not provide a comprehensive account of repository licenses or reuse conditions.
These distinctions matter: publishing code does not by itself reveal the data, weights, or methods used to train a model. ITPro contrasted DeepSeek’s move with Meta’s Llama, which it characterized as open weights without the training code or actual training datasets. That comparison describes the reporting at the time; it is not a comprehensive or current audit of either project’s releases or terms.
“Open-source AI” is also a contested label. Open UK CEO Amanda Brock said AI components do not all fit neatly into traditional open-source definitions and suggested thinking in terms of gradients or “shades of openness.” That is Brock’s framing, rather than a settled universal standard. A useful comparison asks separately whether code, weights, data, and methods are available, and under what terms.
Could the release give competitors a scare?
Pullen argued that DeepSeek could use openness as a competitive signal: “I think DeepSeek can probably feel comfortable giving their competitors a scare by doing stuff others won’t do – it does diminish their edge, but they’re not wholly a model company.” This is his interpretation of the strategic trade-off, not evidence that competitors changed their plans or that the release produced a measurable market effect.
Peter Schneider, senior product manager at Qt Group, called the move “a welcome step toward greater openness in AI development,” and said: “If they wanted to go the extra mile differentiating themselves, releasing their full training data and methodologies would certainly set a new standard for transparency in the AI race”. His remarks underline the gap between sharing some model-related code and disclosing the materials and methods behind training.
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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteDirk Alshuth, cloud evangelist at emma, said: “Open-source AI models appeal to users because they offer greater flexibility, fine-tuning capabilities, and fewer vendor restrictions. But beyond that, the real advantage comes from the collective intelligence of the global open-source community,” That describes a broader potential benefit of open AI projects; it does not show that all those advantages follow from DeepSeek’s five repositories alone.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the announcement does—and does not—show
The March 2025 report documents a transparency move that experts saw as valuable to developers and potentially significant as a competitive signal. It does not establish that DeepSeek made its full development process open, that competitors were actually frightened into responding, or that the repositories remain unchanged and actively maintained today.
For readers assessing any AI release, compare like with like: source code, weights, training data, training methods, and license or reuse terms. The available reporting supports a claim about five repositories announced in March 2025—not a claim about DeepSeek’s complete or current openness.
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