77 guides available in the DeepSeek directory
How to access DeepSeek models through OpenRouter, Together AI, Fireworks AI, and other third-party providers with pricing comparison and integration examples.
Using DeepSeek R1's reasoning for solving Mathematical Olympiad problems: number theory, combinatorics, geometry, and algebra with detailed step-by-step solutions.
How to use DeepSeek V3 for producing high-quality, SEO-optimized content: blog posts, landing pages, product descriptions, meta tags, and content clustering strategies.
Complete guide to building autonomous AI agents using DeepSeek's function calling API, including tool definition, multi-step reasoning, error recovery, and agent evaluation.
How to use DeepSeek R1's reasoning for competitive programming: solving algorithmic challenges, optimizing solutions, analyzing time complexity, and preparing for coding interviews.
Using DeepSeek V3 to generate test cases, write automated tests, create test data, perform exploratory testing analysis, and build testing strategies for complex applications.
Strategies for minimizing DeepSeek API costs while maintaining output quality: caching, batching, model selection, prompt optimization, and usage monitoring.
How to use DeepSeek models for cybersecurity tasks: vulnerability scanning, threat modeling, incident response analysis, secure code review, and security documentation.
Techniques for effectively managing DeepSeek V3's context window: chunking strategies, context compression, sliding window approaches, and priority-based context selection.
Guide to using DeepSeek R1 for academic research: analyzing papers, extracting methodologies, comparing findings, generating literature reviews, and identifying research gaps.
How to use DeepSeek models as the LLM backbone in LangChain and LlamaIndex frameworks for building AI agents, RAG pipelines, and multi-step reasoning chains.
How to use DeepSeek models for data engineering tasks: writing complex SQL queries, designing ETL pipelines, optimizing database performance, and building data models.
Guide to using DeepSeek's vision and multi-modal capabilities for image understanding, document analysis, chart interpretation, and visual question answering.
End-to-end guide to building Retrieval-Augmented Generation systems with DeepSeek V3, covering vector databases, embedding strategies, chunking, and retrieval optimization.
Advanced prompt engineering techniques specific to DeepSeek R1's reasoning model, including think tag optimization, chain-of-thought control, and reasoning quality verification.
Complete guide to fine-tuning DeepSeek V3 on custom datasets using LoRA/QLoRA, including data preparation, training configuration, evaluation, and deployment.
How to integrate DeepSeek Coder V2 into CI/CD pipelines for automated code review, security scanning, and style enforcement with GitHub Actions and GitLab CI examples.
Guide to running DeepSeek R1 distilled variants (1.5B, 7B, 8B, 14B, 32B, 70B) on consumer GPUs and CPUs using Ollama, llama.cpp, and vLLM with quantization strategies.
Step-by-step guide to setting up the DeepSeek API in both Python and TypeScript projects, with examples for chat completion, streaming, function calling, and JSON mode.
A comprehensive comparison of DeepSeek R1 (reasoning model) vs V3 (general-purpose model), with benchmarks, pricing, and use case recommendations for choosing the right model.
Comprehensive written guide covering R1 setup, Deep Think mode, API usage, and practical coding examples for developers.
Step-by-step DataCamp tutorial on local deployment with Ollama including installation, model selection, and API usage.
Quick-start guide for running DeepSeek R1 via Together AI's API with code examples in Python and JavaScript.
SitePoint's updated 2026 guide covering Ollama and vLLM deployment paths with detailed hardware requirements.