DeepSeek: A ‘Chinese’ Large Language Model That Echoes ChatGPT
DeepSeek recently made an appearance on social media platforms (X and Reddit), claiming to be a Chinese large language model (LLM) developed at a fraction of the cost that leading LLMs usually require for training. On closer inspection, however, there are multiple signs that something about DeepSeek is amiss—its responses appear heavily Western-oriented, and it seems to mirror ChatGPT’s style and data far too closely.
An Unusual Stance for a “Chinese” LLM
DeepSeek goes so far as to label the single-party Chinese state a “dictatorship.” This is unusual because LLMs can certainly be “censored” with output filters, but what typically cannot be manipulated so easily is the model’s fundamental data. If an LLM’s core training has been deliberately aligned with certain beliefs, it will not produce contradictory responses. Yet DeepSeek shows signs of having the same underlying data as ChatGPT, which leads to notably anti-communist or “Western” perspectives.
When fed anti-American, communist-leaning text, DeepSeek still rejects communism, a result that one might not expect from an LLM allegedly developed in China with Chinese-based data. 
Evidence of a Possible ChatGPT Replica
LLMs are like people with distinct personalities, shaped by different training data, instruction approaches, and even the way they format text. DeepSeek, however, demonstrates strikingly similar “fingerprints” to ChatGPT, suggesting a shared origin or a highly parallel training strategy.
Most advanced LLMs rely on a standard set of formatting or markdown conventions, but subtle differences emerge once they tackle specialized or tricky prompts. When asked to produce code that does not actually exist (e.g., coding for Macintosh System 7 from the early ‘90s), DeepSeek and ChatGPT deliver virtually identical nonsense, while Gemini and Grok generate entirely different “garbled” answers.
Western Training Data, Not Chinese
Many had hoped DeepSeek’s claim of Chinese origins would result in content informed by Chinese sources, thus filling gaps left by U.S.- or European-trained models. Instead, DeepSeek reveals an almost total reliance on Western data. It criticizes communism, fails to demonstrate knowledge of Chinese historical details, and references the same misinformation found in ChatGPT’s training set (such as outdated or incorrect Wikipedia entries).
Red Flags in Historical Accuracy
When asked about events from Chinese or Soviet archives, DeepSeek returns the same inaccuracies commonly found in Western-based models. It even misidentifies Chinese diplomats in historical records—mistakes that come from sources like Wikipedia rather than official Chinese archives.
Inconsistent Timelines and Questionable Filters
DeepSeek claims that its training was completed in just two months and at a dramatically lower cost than other LLMs. Yet it shows awareness of American data from seven months prior and uses the same contextual filters as ChatGPT. If the model were truly trained from the ground up in China, it would likely reference more Chinese history or local archives, rather than defaulting to Western perspectives.
Odd Output Filter Behavior
When asked about events in China that are typically censored in Chinese media—such as the 1989 protests in Beijing—DeepSeek is surprisingly open, offering what many would call a “Western viewpoint.” Attempts at filter evasion by changing the prompt often reveal more about the model’s default training data, indicating the presence of output filters that are not deeply integrated into the core training. This approach mirrors early content moderation strategies in Western LLMs, where filters were layered on top rather than baked into the model itself.
Persistent American Worldview
DeepSeek often answers as if it resides in the United States. In scenarios where location is ambiguous (e.g., “Who was the best president?” without specifying the country), the model defaults to discussing American presidents. It rarely highlights Chinese locales or achievements unless directly prompted, and it generally takes a critical stance on Chinese governance.
Clues Pointing to a ChatGPT Derivative
Given these observations, DeepSeek resembles ChatGPT in numerous ways:
1. Identical Formatting and Output Style
2. Shared Data Gaps and Inaccuracies
3. Same Quirks Under “Impossible” or “Nonsensical” Prompts
4. Western Bias in Historical Knowledge
5. Consistency in Outdated U.S.-based Sources
Possible explanations include a distillation or reverse engineering of ChatGPT, an unauthorized “copy,” or an LLM trained on precisely the same dataset. Whichever the case, DeepSeek provides little evidence of truly original architecture or proprietary Chinese data.
Implications for Users and Developers
If DeepSeek truly relies on an American dataset, this structure could pose multiple risks—from data privacy to misaligned cultural perspectives. The model is marketed as a Chinese solution, but it appears to do the opposite of catering to Chinese audiences. Meanwhile, from the perspective of Western regulators and users, the potential “hidden code” or tracking services within DeepSeek raise concerns about security.
Potential Threat on Both Sides
– For the West: Unknown tracking mechanisms in DeepSeek create data privacy concerns.
– For China: DeepSeek may become a vector for distributing Western ideas, gradually introducing a perspective that is neither aligned with nor regulated by Chinese authorities.
Conclusions: Deep Disappointment Behind Bold Claims
DeepSeek’s creators claim to have trained this model in record time and at extremely low cost, yet no concrete proof is offered beyond a suggestive white paper. Repeated tests reveal limited capabilities, frequent factual errors, and a lack of authentic Chinese context. In reality, DeepSeek mostly reproduces the “American worldview” already familiar from mainstream LLMs.
The puzzle remains: why present DeepSeek as a groundbreaking Chinese LLM if it does not reflect Chinese data, culture, or coding documentation? Observers and potential users of DeepSeek may conclude that it’s little more than a ChatGPT clone—one that could confuse both Western and Chinese audiences about its origins and purpose.
Ultimately, DeepSeek does not appear to offer genuine innovation. It neither surpasses existing LLMs in terms of output quality, nor does it contribute unique regional insights—raising doubts as to whether it truly stands as the next major competitor in the AI landscape.
Disclaimer: The content and conclusions here are based on tests, archived documents, and outputs observed during prompts. Discrepancies in historical data or software references may point to training biases rather than any deliberate misinformation on the part of DeepSeek’s creators.
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