1. DeepSeek's models are completely open source.
DeepSeek has only open-sourced some of its models (such as DeepSeek-V2), but this does not mean that all of their technologies and models are completely open source. They may also have some proprietary models and technologies for commercialization or specific applications. Therefore, it is important to understand the specific scope of their open source strategy. Of course, it is not ruled out that DeepSeek will adjust its open source policy in the future.
2. DeepSeek's model capabilities have surpassed all AI competitors.
Wrong.
DeepSeek's models perform well on certain benchmarks and specific tasks, but the entire field of large language models is still developing rapidly, and different models have their own advantages in different capabilities and application scenarios. Don't blindly think that DeepSeek has surpassed all competitors.
3. DeepSeek's models perform consistently in both language and cultural contexts.
The performance of large language models is often affected by the language coverage and cultural bias of the training data. At present, DeepSeek is indeed remarkable in understanding Chinese, but it does not mean that it is also the same in other languages.
4. DeepSeek only serves the Chinese market.
At present, this is wrong. DeepSeek's technology and products have global potential. And it has attracted the attention of international giants such as Amazon, Microsoft, and DeepSeek has also begun to focus on the international market.
5. DeepSeek only relies on API call charges.
At present, DeepSeek's business model relies on API call charges. However, it is not ruled out that DeepSeek provides customized AI solutions for corporate customers, or explores other business models.
6. DeepSeek's model inference speed and cost have reached the optimal level.
Combined with the current large models of various companies, the inference speed and cost of large language models are continuously optimized. Although DeepSeek may be constantly improving its model architecture and deployment strategy to improve efficiency and reduce costs. Not only that, other companies' large models, such as OpenAI, Gemini, etc., are reducing costs and increasing efficiency.
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