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DeepSeek R1 Explained: A Beginner-Friendly Guide (2025)

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3 months ago

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Mike Loo

Kristine Tang
Technology Jounalist & Hardware Reviewer

Kristine Tang covers the intersection of gaming and technology at Bright Side of News. Known for her approachable breakdowns of complex hardware, she focuses on helping new creators understand the tools professionals use — from GPUs to capture cards. When she’s not benchmarking devices, she’s exploring how tech empowers the next generation of streamers.

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Deepseek R1 explained

In early 2025, a new name burst onto the AI scene: DeepSeek R1.

Stock markets shifted. Social media lit up with debates. Headlines proclaimed that “China’s AI is shaking up Silicon Valley.”

If you don’t follow tech closely, you’ve probably seen the buzz without understanding what’s actually happening:

  • What even is DeepSeek R1?
  • Why does everyone keep calling it a “reasoning model”?
  • What’s the big deal about “open-source”?
  • And should regular people actually care about any of this?

This article cuts through the noise. We’ll cover the technical facts, but explain them in normal human language—with simple analogies (think: kitchens, restaurants, and food delivery) to make everything click.

By the end, you’ll understand what DeepSeek R1 actually is, what makes it different from other AI models, where it excels and where it falls short, and how you can use it yourself—even if you’re a designer, writer, or just curious about AI.

What Is DeepSeek AI and DeepSeek R1?

DeepSeek is a Chinese AI company that builds large language models—the same kind of technology behind ChatGPT (from OpenAI), Claude (from Anthropic), and Gemini (from Google).

DeepSeek R1 is their reasoning-focused AI model. Here’s the simplest way to think about it:

  • Most chatbots focus on sounding fluent and natural.
  • DeepSeek R1 focuses on thinking through problems step-by-step.

On the technical side, R1 is a large language model (LLM) that was trained heavily using reinforcement learning—a method that rewards the AI when its reasoning leads to correct answers. What makes it unusual is that DeepSeek released the model with open-source weights under an MIT-style license. That means anyone can download it and run it on their own computers.

Think of it this way:

DeepSeek R1 = a very smart “logic brain” that you can actually own.

Instead of being locked away on a company’s servers, R1 is more like a brain blueprint that anyone is allowed to copy and use.

When Was DeepSeek R1 Released?

DeepSeek R1 launched officially on January 20, 2025.

The timing matters. R1 arrived right in the middle of a heated global race to build better reasoning models. OpenAI had just released its o1 reasoning models. Anthropic was pushing updates to Claude 3.5. Google was refining Gemini 2.0 with a focus on understanding images, videos, and documents. Meta and others were improving Llama and other open-source models.

DeepSeek R1 jumped into this crowded field with a bold claim: “We can reason as well as the big commercial models—but ours is open and free for everyone to run.” That’s what sparked all the attention.

How Does DeepSeek R1 Work (in Plain English)?

Most older AI chatbots work like supercharged autocomplete. They look at the text you’ve given them so far and predict what word should come next based on patterns they learned during training.

Normal AI vs “Reasoning” AI

This approach can sound very smooth and fluent. But it has some problems:

  • It sometimes gives confident answers that are completely wrong.
  • It “hallucinates” facts—making up information that sounds plausible but isn’t real.
  • It doesn’t really think. It just predicts what text is likely to come next.

DeepSeek R1 belongs to a newer category called “reasoning models.” These models are trained to break complex problems into smaller steps, think through each step carefully, and then arrive at an answer. DeepSeek used reinforcement learning to train R1. Essentially, they rewarded the model whenever its step-by-step reasoning led to correct answers—especially on challenging math, logic, and coding problems.

Here’s the difference in simple terms:

Old AI: “I’ll guess what sounds right based on what I’ve seen before.”
R1-style AI: “Let me think out loud, step by step, and work this out.”

That’s why DeepSeek R1 tends to be particularly strong at:

  • Math problems
  • Logic puzzles
  • Coding tasks
  • Complex multi-step questions
  • Analysis-heavy work

Open Weights and Model Sizes (The Brain You Can Download)

DeepSeek didn’t just build R1 and keep it to themselves. They have publicly released the R1 weights and several distilled models on GitHub, so anyone can download and run them locally.—the actual trained parameters—to the public under a permissive MIT license.

In AI terms, the full R1 model is a mixture-of-experts system with around 671 billion parameters (but only ~37B are active at any time due to the Mixture-of-Experts architecture). DeepSeek also released distilled (smaller) versions of the model, ranging from roughly 1.5 billion up to 70 billion parameters. “Distilled” means they let the big model teach smaller models, so you end up with something lighter but still capable.

For non-technical folks, here’s what those numbers mean in practice:

  • Small models (1.5B, 7B parameters) can run on regular laptops
  • Medium models (14B, 32B parameters) need a stronger PC or a dedicated GPU
  • Large models (70B, full R1) require server-grade hardware

This is why people keep talking about R1 as a big deal. It’s not just a model you can chat with online. It’s a model you can download, own, and run yourself.

Cloud vs Local vs Third‑Party (Restaurant Analogy)

This is the part that confuses most people, so let’s be crystal clear.

There are three main ways to use DeepSeek R1:

  1. Cloud via DeepSeek’s own service (their official chat interface or API)
  2. Cloud via third-party platforms like Hugging Face (other companies hosting R1)
  3. Locally on your own device (running R1 on your own computer)

The model itself is the same “brain” in all three cases. What changes is where the actual computing happens.

Let’s use a food analogy to make this stick.

🍳 Running R1 Locally = Cooking at Home

You download the recipe (the R1 model weights—completely free). You buy ingredients once (your computer hardware). You cook in your own kitchen (your CPU or GPU does all the work).

The result? Completely private—no data leaves your computer. No ongoing costs per use. You control everything. But if your kitchen is small (weak laptop), the cooking might be slow or limited, and you have to do a bit of setup.

🍽 DeepSeek Official API = Eating at the Restaurant

Same recipe (R1), but DeepSeek runs the model on their powerful cloud GPUs—their “kitchen.” You just send requests over the internet and get responses back.

Here, the model itself is still free, but running it on big cloud machines costs money (electricity, hardware, maintenance). So DeepSeek charges usage fees, typically per million tokens processed. You’re not paying for the recipe—you’re paying for the chef, the gas, the electricity, and the restaurant space.

🚚 Third-Party Platforms = Food Delivery Apps

Third-party companies—cloud platforms and AI infrastructure providers—can also host DeepSeek R1 on their own servers. They download the free model, run it on their hardware, expose an API or web interface, and bill you based on your usage.

Why would anyone use a third party instead of DeepSeek directly? They might be cheaper in your region, offer extra features (dashboards, logging, fine-tuning options), bundle multiple models (R1 + GPT + Claude) in one interface, or let you run custom versions of R1. Third parties are selling compute power, convenience, and tooling—not the model itself.

DeepSeek R1 Restrictions and Limitations

DeepSeek R1 is impressive, but it’s not perfect. It has clear technical and practical limitations.

Technical Limitations

Weaker Creative and Emotional Writing

R1 excels at logic, but it struggles with birthday messages, romantic texts, marketing copy, and social media captions. These often feel flat or robotic. If GPT or Claude write like skilled human copywriters, R1 writes like a serious engineer trying to sound friendly.

English Tone Can Feel Stiff

Even when R1’s answers are technically correct, the language can repeat phrases awkwardly, feel unnaturally formal, or miss the “vibe” or style you’re going for. Claude and GPT are noticeably better if tone and voice matter to you.

No Multimodal Support (Text-Only)

R1 cannot look at images, read charts or PDFs directly, watch videos, or listen to audio. It’s a text-only reasoning model. If you need an AI that can process images or other media, you’ll need something like GPT-4o or Gemini.

Heavy Models Need Heavy Hardware

You can run small R1 models on a laptop, but the 32B or 70B versions require serious GPUs (often needing 24GB to 48GB of video memory). Not everyone has that kind of machine. So when people say “anyone can run it locally,” that’s only really true for the smaller versions.

Still Hallucinates and Overthinks

Even with better reasoning training, R1 can still give wrong answers confidently, “think out loud” for way too long, and generate very verbose chains of thought. It’s still an AI language model—not a calculator or an oracle.

Policy & Access Limitations (Official Cloud Version)

The open-weight version you run locally is one thing. The official cloud version is another.

According to user reports and media coverage, DeepSeek’s official cloud interface filters sensitive political content in compliance with Chinese regulation. The model may initially generate an answer, then delete it and replace it with a “Sorry, I can’t answer that” message. Several countries and regulators have raised data security and privacy concerns, leading to investigations or outright bans of DeepSeek on government devices.

⚠️ Important Nuance:

These restrictions apply mainly to DeepSeek’s official servers and apps. People running the open-source R1 locally report they can remove or bypass those filters.

So: Official DeepSeek means more content control and policy constraints. Local R1 means more freedom, but also more responsibility.

How Is DeepSeek R1 Different from GPT, Claude, Gemini & Others?

Here’s a straightforward comparison, using personality metaphors to make the differences clear.

DeepSeek R1 vs OpenAI (GPT-4o, o1)

OpenAI’s o1 is probably still the gold standard for pure reasoning quality. GPT-4o is the best all-rounder: strong at coding, writing, and multimodal tasks.

DeepSeek R1 aims for similar reasoning quality but as an open-source option. It’s cheaper to run, especially if you self-host, but less polished in language and user experience. Think of it like this: OpenAI is a luxury brand laptop. R1 is a powerful DIY PC that anyone can assemble for cheap.

DeepSeek R1 vs Claude 3.5

Claude 3.5 is the best writer, excellent at editing, great with long documents, and very natural in tone. R1 is better at pure logic in many open benchmarks (especially per dollar spent), but worse at emotional or stylish writing.

Claude is your friend who’s a talented editor and storyteller. R1 is your friend who crushes math contests.

DeepSeek R1 vs Google Gemini 2.0

Gemini 2.0 is a multimodal system: it understands images, PDFs, charts, and videos, and is tightly integrated with Google’s suite of tools. R1 is text-only, but better suited for logic and coding tasks if you don’t need image understanding.

Gemini is AI that sees and reads. R1 is AI that thinks in text.

DeepSeek R1 vs Llama / Mistral / Qwen (Other Open Models)

Llama 3 and 3.1 are the best general-purpose open-source base for many applications. Mistral offers very efficient small models, good for edge devices. Qwen provides strong multilingual performance, especially for Asian languages.

DeepSeek R1 stands out as the reasoning specialist within the open-source family. Other models are Swiss Army knives. R1 is one very sharp logic blade.

How to Run DeepSeek R1 Locally (Beginner-Friendly Steps)

Let’s get practical. Here’s how to actually run R1 on your own computer.

Easiest Path: LM Studio (No Coding Required)

LM Studio is a free desktop app for Windows, Mac, and Linux that lets you run AI models locally with a simple interface.

Getting started is straightforward. First, go to the LM Studio website and download and install it like any normal app. Open the app and go to the Models tab. Type “deepseek r1” or “deepseek-r1-distill-7b” into the search box, and you’ll see several versions pop up.

Choose a model size based on your hardware:

  • 1.5B or 7B works on almost any modern laptop
  • 14B is better with 16GB+ RAM or a decent GPU
  • 32B needs a strong GPU (24-48GB VRAM)

For most people, start with the 7B version—it offers good performance without being too heavy. Running the full 671B model requires serious GPU power and multi-GPU setups—far beyond normal consumer PCs.

Click download. The app downloads the model files (a few gigabytes) and sets everything up automatically. Then click “Open in Chat,” type your question, and watch your own machine do all the thinking.

No internet needed once it’s downloaded. No API keys. No monthly fees. It’s your own private AI.

Slightly More Advanced: Ollama (Great on Mac/Linux)

If you’re comfortable with basic terminal commands, install Ollama from their website and run these two commands:

bash

ollama pull deepseek-r1:7b

ollama run deepseek-r1:7b

This approach is lighter and more script-friendly if you want to automate things.

What About Phones?

Right now, running full R1 on phones is tough because of storage size, RAM limits, and weaker processors. But smaller distilled models may eventually make it into mobile apps as phone hardware continues to improve.

Why DeepSeek R1 Actually Matters

DeepSeek R1 isn’t just another chatbot. It represents three important shifts in AI.

First, it’s reasoning-focused. More thinking, less guessing. R1 is designed to work through problems step-by-step rather than just sounding fluent.

Second, it’s an open-weight, MIT-licensed model. The public can download, inspect, modify, and run a model that competes with closed, commercial systems. This level of openness at this performance level is new.

Third, it enables local-first possibilities. Regular people and small teams can run strong reasoning AI without sending their data to a big tech company.

Is R1 perfect? Not even close. It’s not the best writer. It can’t see images. Its official services face censorship and regulatory concerns. It still makes mistakes.

But it pushes the boundary of what open-source AI can do, especially for reasoning tasks. It also puts real competitive pressure on the big Western labs by proving something important: “You don’t need billions in subscription revenue to build serious AI.”. Several technical analyses now treat DeepSeek V3 and R1 as a serious paradigm shift in how we think about cost-efficient, open-weight AI.

For everyday people, R1 means more choice in AI tools, more options for privacy, more competition in the market, and a clearer view of where this technology is actually headed.

Frequently Asked Questions

Is DeepSeek R1 free?
Yes. The model itself is free and open-source. Running it locally on your hardware is free with no per-use cost. Using it via cloud APIs means you pay for compute time (GPU usage), not for the model itself.
Is DeepSeek R1 better than ChatGPT?
It depends on what you need. For pure logic, math, and some coding tasks, R1 can be very competitive—especially when you factor in cost. For smooth writing, creative text, and multimodal tasks, ChatGPT (GPT-4o) is still ahead.
Can I run DeepSeek R1 on a normal laptop?
Yes, as long as you choose a small or medium model. The 1.5B or 7B versions work on most modern laptops. The 14B version needs more RAM. The 32B and larger versions are better suited for strong GPU desktops or servers.
Is my data safe with DeepSeek R1?
If you run R1 locally, your data never leaves your device—that’s the most private option. If you use DeepSeek’s cloud or a third-party API, your data goes through their servers, so you’re trusting them just like with any other cloud AI. Some regulators have raised concerns about data privacy on DeepSeek’s official services.
Does DeepSeek R1 support images or video?
No. R1 is currently text-only. If you need an AI that can look at images or videos, you’ll need something like GPT-4o or Gemini 2.0.
Why are people calling DeepSeek R1 a “big deal”?
Because it combines strong reasoning, an open-source license, downloadable weights, multiple model sizes, and local deployment support. That combination didn’t really exist at this level before R1.
Does DeepSeek R1 replace GPT / Claude / Gemini?
No. It adds another option. Use GPT or Claude for writing-heavy, polished tasks. Use R1 for logic-heavy, cost-sensitive, or privacy-sensitive tasks. Use multimodal models for image and video understanding. You don’t have to pick a single “winner”—you pick the right tool for the job.

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