Since a major part of the article covers cost expenditures, I am going to go there.
I don't think it is possible to trust DeepSeek as they haven't been honest.
DeepSeek claimed "their total training costs amounted to just $5.576 million"
SemiAnalysis "Our analysis shows that the total server CapEx for DeepSeek is ~$1.6B, with a considerable cost of $944M associated with operating such clusters. Similarly, all AI Labs and Hyperscalers have many more GPUs for various tasks including research and training then they they commit to an individual training run due to centralization of resources being a challenge. X.AI is unique as an AI lab with all their GPUs in 1 location."
SemiAnalysis "We believe the pre-training number is nowhere the actual amount spent on the model. We are confident their hardware spend is well higher than $500M over the company history. To develop new architecture innovations, during the model development, there is a considerable spend on testing new ideas, new architecture ideas, and ablations. Multi-Head Latent Attention, a key innovation of DeepSeek, took several months to develop and cost a whole team of manhours and GPU hours.
The $6M cost in the paper is attributed to just the GPU cost of the pre-training run, which is only a portion of the total cost of the model. Excluded are important pieces of the puzzle like R&D and TCO of the hardware itself. For reference, Claude 3.5 Sonnet cost $10s of millions to train, and if that was the total cost Anthropic needed, then they would not raise billions from Google and tens of billions from Amazon. It’s because they have to experiment, come up with new architectures, gather and clean data, pay employees, and much more."
Source: https://semianalysis.com/2025/01/31/deepseek-debates/