Artificial intelligence (AI) is changing the way we solve problems, and DeepSeek DeepThink R1 is a cutting-edge AI model designed to make this transformation even more impactful. Developed by DeepSeek, this model excels at tasks like understanding language, analyzing data, and supporting decision-making. In this blog, we’ll break down what DeepThink R1 is, how it works, and where it can be used.
What is DeepSeek DeepThink R1?
On January 20, 2025, DeepSeek DeepThink R1 was released, marking a major advancement in AI reasoning and decision-making. This model is designed to handle complex tasks with exceptional efficiency and effectiveness.

Exceptional Reasoning Capabilities
DeepSeek DeepThink R1 stands out for its ability to solve challenging reasoning tasks. It performs exceptionally well in areas like logical inference, mathematical problem-solving, and real-time decision-making. For example, it achieves a 79.8% pass rate on the American Invitational Mathematics Examination (AIME) and a 97.3% pass rate on the MATH-500 dataset. These results are comparable to OpenAI’s o1 model, proving its strength in the AI reasoning space.
Efficient Design
Despite having 671 billion parameters, DeepSeek DeepThink R1 is highly efficient. Only 37 billion parameters are activated per forward pass, thanks to its Mixture of Experts (MoE) approach. This design allows the model to scale effectively without a significant increase in computational costs. In simple terms, it delivers high performance while using fewer resources.
Open-Source and Affordable
One of the key features of DeepSeek DeepThink R1 is its open-source availability. Released under the MIT license, the model allows researchers and developers to inspect, modify, and use the code for commercial purposes. This level of openness is rare in the AI field and encourages innovation and collaboration.
Additionally, DeepSeek DeepThink R1 is highly cost-effective. Built with a budget of just $6 million, it offers a cloud-based API service at prices much lower than industry standards. This makes advanced AI capabilities accessible to small businesses and individual developers.
Advanced Training Process
The training process for DeepSeek DeepThink R1 is both innovative and effective. It uses reinforcement learning (RL), a method that allows the model to learn through trial and error without human intervention. This approach helps the model refine its reasoning strategies over time.
The training involves multiple stages, including a cold-start phase before RL. This multi-stage process ensures the model is robust and avoids issues like poor readability and language mixing.
Easy Accessibility
DeepSeek DeepThink R1 is available on Azure AI Foundry and GitHub, making it easy to integrate into existing systems. These platforms are trusted, scalable, and enterprise-ready, ensuring compatibility and reliability for businesses.
For those without local resources, the model can be accessed for free through chat.deepseek.com. Alternatively, the cloud-based API service provides an affordable and convenient way to use its capabilities.
How Does DeepThink R1 Work?
DeepThink R1 works through a combination of advanced technology and training. Here’s a Detaild explanation of its key components:
1. Neural Network Architecture
The model is built on a neural network, a system designed to mimic how the human brain works. This includes components like transformers and convolutional neural networks (CNNs), which help it process data efficiently.
2. Training on Data
DeepThink R1 is trained on large datasets to recognize patterns and relationships. This training happens in two ways:
- Supervised Learning: The model learns from labeled data, where the correct answers are provided.
- Unsupervised Learning: The model finds patterns on its own without labeled data.
This training helps the model improve its accuracy over time.
3. Natural Language Processing (NLP)
One of the key features of DeepThink R1 is its ability to understand and generate human language. It uses techniques like tokenization (breaking text into smaller parts) and attention mechanisms (focusing on important parts of the text) to process language effectively. This makes it ideal for tasks like translation, summarization, and answering questions.
4. Data Analysis
The model can analyze both structured data (like databases) and unstructured data (like text or images). It identifies trends, makes predictions, and provides insights. For example, in finance, it can analyze market trends or detect fraud, while in healthcare, it can assist in diagnosing diseases or recommending treatments.
5. Decision-Making Support
DeepThink R1 helps users make informed decisions by providing data-driven recommendations. This is especially useful in fields where quick and accurate decisions are critical, such as logistics, healthcare, and finance.
6. Integration with Existing Systems
The model can be easily integrated into existing systems and applications through APIs (Application Programming Interfaces). This allows businesses to use its capabilities without changing their current workflows.
7. Continuous Learning
DeepThink R1 is designed to improve over time. As it encounters new data, it updates its knowledge and refines its performance. This ensures it stays effective and up-to-date.
Where Can DeepThink R1 Be Used?
DeepThink R1 has a wide range of applications across industries. Here are some examples:
- Customer Support: It can automate responses to customer inquiries, providing quick and accurate support.
- Healthcare: It assists doctors in diagnosing conditions, recommending treatments, and monitoring patients.
- Finance: It analyzes market trends, assesses risks, and detects fraudulent activities.
- E-commerce: It personalizes shopping experiences and optimizes supply chains.
- Research: It accelerates data analysis and helps researchers test hypotheses faster.
DeepSeek-R1: Reinforcement Learning for Stronger AI Reasoning

How to Set Up and Use the DeepSeek R1 API
The DeepSeek R1 API is a powerful tool for integrating AI into your projects. This guide will walk you through the steps to set it up, from obtaining your API key to making your first API call. We’ll also cover the pricing structure to help you understand its cost-effectiveness.
Setting Up the DeepSeek R1 API
To use the DeepSeek R1 API, you need to obtain an API key and configure endpoints for your chosen programming language. Here’s how to get started.
Step 1: Obtain Your API Key
- Log in to the DeepSeek Open Platform: Visit the platform and sign in to your account.
- Go to the API Keys Section: Navigate to the “API Keys” section in the sidebar.
- Create and Copy Your API Key: Generate a new API key and copy it immediately. Store it securely, as it won’t be displayed again.
Important: Always keep your API key safe. Avoid sharing it publicly or storing it in unsecured locations.
Step 2: Configure Endpoints and Make API Calls
The DeepSeek R1 API is designed to work seamlessly with OpenAI’s SDK, making it easy to integrate into various programming languages. Below are examples of how to set up and use the API in different environments.
Using cURL for Quick Testing
For quick testing or command-line usage, you can use cURL. Here’s an example:
curl https://api.deepseek.com/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer <DeepSeek API Key>" \
-d '{
"model": "deepseek-chat",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"}
],
"stream": false
}'
Note: Replace <DeepSeek API Key>
with your actual API key.
Using Python for Advanced Applications
For more robust applications, Python is a great choice. Here’s a basic example of how to set up and make an API call:
# Please install OpenAI SDK first: `pip3 install openai`
from openai import OpenAI
client = OpenAI(api_key="<DeepSeek API Key>", base_url="https://api.deepseek.com")
response = client.chat.completions.create(
model="deepseek-chat",
messages=[
{"role": "system", "content": "You are a helpful assistant"},
{"role": "user", "content": "Hello"},
],
stream=False
)
print(response.choices[0].message.content)
Note: Replace <DeepSeek API Key>
with your actual API key.
Node.js Example
// Please install OpenAI SDK first: `npm install openai`
import OpenAI from "openai";
const openai = new OpenAI({
baseURL: 'https://api.deepseek.com',
apiKey: '<DeepSeek API Key>'
});
async function main() {
const completion = await openai.chat.completions.create({
messages: [{ role: "system", content: "You are a helpful assistant." }],
model: "deepseek-chat",
});
console.log(completion.choices[0].message.content);
}
main();
By following these steps, you can quickly set up and start using the DeepSeek R1 API in your projects. For more advanced usage and best practices, refer to the official documentation.
DeepSeek R1 API Pricing
Understanding the pricing structure is important for planning your AI integration. DeepSeek R1 offers a cost-effective solution compared to other leading AI models. Here’s a detailed breakdown of the pricing:
Pricing Details
DeepSeek provides pricing in both USD and CNY, with costs calculated per 1 million tokens. Below is a comparison of the two main models:

Model | Context Length | Max COT Tokens | Max Output Tokens | Input Price (Cache Hit) | Input Price (Cache Miss) | Output Price |
---|---|---|---|---|---|---|
deepseek-chat (USD) | 64K | – | 8K | $0.014 | $0.14 | $0.28 |
deepseek-reasoner (USD) | 64K | 32K | 8K | $0.14 | $0.55 | $2.19 |
