DeepSeek
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How DeepSeek’s $14B V3 model changes LLM cost efficiency
DeepSeek-V3 training required only 2.788 million H800 GPU-hours costing $5.576 million, shifting the cost curve for enterprise AI. This efficiency impacts cloud…
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DeepSeek V3 architecture and enterprise LLM deployment economics
DeepSeek-V3 utilizes a 671B parameter Mixture-of-Experts architecture to drive inference efficiency. DeepSeek-V4-Flash offers significant cost advantages for enterprises, with input costs at…
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Reasoning token economics and the DeepSeek price gap
OpenAI reasoning models charge for internal thought tokens at standard output rates, creating significant hidden costs. DeepSeek R1 offers massive savings with…
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DeepSeek’s efficiency advantage in Chinese enterprise cloud deployments
DeepSeek-V3 utilizes a Mixture-of-Experts architecture with 671 billion parameters to achieve high performance at a low cost. This design allows for a…
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DeepSeek-V4-Pro architecture and the competitive coding frontier
DeepSeek-V4-Pro utilizes a Mixture-of-Experts architecture with 256 routed experts to achieve a 55.4 percent score on SWE-bench Pro. This model provides significant…