DeepSeek : The Open Model That Changed the Cost Curve
Language: English
Published by Finnoybu Press, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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nach der Bestellung gedruckt Neuware - Printed after ordering.
Seller Inventory # 9798950533112
- Title
- DeepSeek : The Open Model That Changed the Cost Curve
- Author
- Ken Tannenbaum
- Publisher
- Finnoybu Press
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798950533112
- Item weight
- 636 grams
- Dimensions
- 235x191x18 mm
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:
- Understand the family. V4 Pro, V4 Flash, the R1 reasoning line, the distilled models (1.5B to 70B), Janus, Prover-V2, OCR - every model, what makes each architecturally distinct, and which one to use when.
- Use the web app. chat.deepseek.com end-to-end: thinking mode, file uploads, code interpreter, web search. Plus the mobile apps and browser extensions.
- Build with the API. Authentication, model selection, prompt caching (the 80% cost saver), tool calling, JSON mode, FIM completion, streaming. Every API feature with working code.
- Master reasoning. When to use thinking mode, how to design agent workflows around it, and the patterns that make reasoning models cost-effective.
- Self-host if you need to. Ollama for laptops, vLLM for production, BentoML for multi-GPU deployments. The hardware reality and the deployment paths that work.
- Use it for your world. Targeted chapters for developers, researchers, and cost-conscious teams - including DeepSeek-as-a-cost-layer strategies for orgs already on OpenAI or Claude.
- Stay informed. Honest coverage of the China question, what DeepSeek censors, the geopolitical context, and how to evaluate whether DeepSeek fits your team's risk profile.
- 60+ ready-to-use prompt templates organized by category - coding, reasoning, agents, structured output, and cost-optimized cache-friendly patterns.
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.
"Synopsis" may belong to another edition of this title.
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