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The model that broke the cost curve. The only book that explains it end-to-end.
In December 2024, a small Chinese AI lab released DeepSeek-V3 - a frontier-class language model trained for under $6 million when its Western competitors spent $50 million or more. A month later they released R1, a reasoning model that rivaled OpenAI's o1 at a fraction of the cost. By April 2026, DeepSeek-V4 Pro and Flash had taken the cost curve another order of magnitude lower while matching the quality of Claude Opus 4.7 and GPT-5.5 on real workloads.
DeepSeek didn't just release a model. It changed what AI is supposed to cost.
DeepSeek: Code, Math, and Reasoning is the comprehensive, up-to-date guide to everything DeepSeek - the chat app, the API, the models, the deployment options, and the strategic implications for teams already paying OpenAI or Anthropic.
What's inside:
Whether you're a developer evaluating DeepSeek for the first time, a tech lead building a multi-model strategy, or a researcher running large-scale prompt experiments, this is the only book you need.
Includes coverage of V4 Pro and Flash, Compressed Sparse Attention, prompt caching strategies, tool calling, JSON mode, FIM, the Janus and OCR specialized models, and every 2026 release.
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