How to Master DeepSeek R1 Prompt Engineering

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In this video, I break down DeepSeek R1, the open-source AI model taking the internet by storm with its unmatched logical reasoning capabilities. Unlike other LLMs, DeepSeek R1 is optimized for advanced problem-solving through a combination of reinforcement learning (RL) and supervised fine-tuning (SFT), making it one of the most structured, step-by-step thinkers in AI today.
This guide includes:

A deep dive into DeepSeek R1's architecture and why it excels in reasoning tasks.
The best practices for prompting DeepSeek R1, including markdown structuring and ideal temperature settings.

A breakdown of each DeepSeek R1 model (from 1.5B to 671B) and what tasks they perform best.
How to craft optimized prompts for coding, math, research, and advanced NLP tasks.
A look at Promptify-R1, a custom GPT designed to generate model-specific DeepSeek R1 prompts effortlessly.

Whether you’re an AI researcher, developer, or prompt engineer, this tutorial will equip you with the tools and insights needed to maximize DeepSeek R1’s reasoning power and improve prompt efficiency.
Discover how to:

✅ Leverage DeepSeek R1’s Chain-of-Thought (CoT) reasoning for step-by-step logical responses.
✅ Use zero-shot prompting techniques to get the best results without example-based inputs.
✅ Optimize AI-generated responses with markdown structuring and precise temperature settings.
✅ Choose the right DeepSeek R1 model based on task complexity (coding, math, research, automation).
✅ Utilize Promptify-R1 to auto-generate effective, structured DeepSeek R1 prompts.

???? About Me: I'm Mark, owner of Prompt Advisers, helping businesses streamline workflows with AI. If you’re looking to master AI prompting and harness the power of DeepSeek R1, this guide is for you!

⏳ TIMESTAMPS

0:00 – Why most people aren’t talking about how to prompt DeepSeek
0:12 – Overview of DeepSeek models, from most powerful to most basic
0:38 – Skipping the deep dive: Focusing only on how to prompt DeepSeek
1:01 – What makes DeepSeek special and why it’s a big deal
1:25 – The unique reasoning ability of DeepSeek R1 models
2:01 – What are quantized & distilled models? (Zipping a model)
2:35 – Best DeepSeek model to install locally
3:18 – Which model size is best for local usage? (14B is a sweet spot)
4:00 – DeepSeek is bilingual, but struggles outside English & Chinese
4:17 – DeepSeek prefers zero-shot prompting (Less context = Better)
4:45 – Structured formatting: Markdown, XML & “Think” tags
5:17 – Ideal temperature settings for DeepSeek models
6:01 – How prompt length changes across model sizes
6:36 – Why DeepSeek R1 models respond better to “Think” and “Answer” tags
7:12 – DeepSeek 671B: The most powerful model’s strengths
8:01 – DeepSeek 70B: Still powerful, but requires more intentional prompts
8:39 – DeepSeek 32B: Struggles with multi-step reasoning
9:10 – DeepSeek 14B: Best local model for decent performance
10:26 – Real-time DeepSeek prompting demo on a local setup
11:14 – DeepSeek 7B & 8B: Only useful for basic outputs
11:52 – DeepSeek 1.5B: Not worth using, better alternatives exist
12:05 – A custom GPT to generate the best DeepSeek prompts for you
13:26 – The DeepSeek cheat sheet: Model capabilities & best prompts

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