The capabilities and usage diversity of an AI tool are closely related to the LLM (Large Language Model) that the AI ​​tool uses. If the LLM of the AI ​​tool performs well in tasks such as coding, natural language, and reasoning, you can complete complex tasks more concisely with that AI tool. When it comes to the most advanced LLMs, OpenAI-o1 is a popular option with high performance that is accepted by everyone. However, DeepSeek R1 introduced on 2025/01/20 and has a performance that competes with the OpenAI-o1 model, started to stand out by offering similar performance at a lower price. If you are curious about the DeepSeek R1 model and want to learn its similarities and differences with OpenAI-o1, we've got you covered!

In this article, we will examine the OpenAI-o1 and DeepSeek R1 models and compare the two models.

Ready? Let's dive in!

TL; DR

  • The DeepSeek R1 is a large language model that was released on January 20, 2025, and has a similar performance to OpenAI-o1.
  • DeepSeek R1 has two versions 70b and 32b to meet the specific needs of its users.
  • You can use the DeepSeek AI chatbot interface to access the DeepSeek R1 model, utilize it as API or integrate it directly into your workflow via TextCortex.
  • DeepSeek R1 and OpenAI o1 models are two different large language models that offer high performance.
  • Although both DeepSeek R1 and OpenAI-o1 have similar performance in benchmarks, DeepSeek R1 model is budget-friendly.
  • If you are looking for a method where you can use DeepSeek and OpenAI-o1 models simultaneously and integrate both into your organization's workflow, TextCortex is the way to go.

What is DeepSeek R1?

DeepSeek R1 is an LLM that was released on January 20, 2025, and stands out with its high performance in benchmarks. DeepSeek R1 offers its users equal performance to the OpenAI-o1 model at much cheaper prices. DeepSeek R1 leverages a unique multi-stage training process to achieve advanced reasoning capabilities. It utilizes a Mixture of Experts (MoE) design with 671 billion parameters, activating 37 billion per forward pass. This architecture stands out for its scalability and efficiency.

What is DeepSeek R1?

DeepSeek R1 Features

DeepSeek R1 offers its users an LLM interface with 671 billion parameters and a 128K context window. The DeepSeek R1 model has been released in two versions, 70b and 32b, to meet the specific needs of its users. If you need high processing power for more complex tasks, it will be useful to leverage the DeepSeek R1 70b version, and the 32b version for tasks that require less processing power.

DeepSeek R1 can perform all the textual output generation and input analysis tasks that a large language model can. In other words, you can use DeepSeek R1 to generate content from scratch or to edit your existing content. Although DeepSeek R1 can perform natural language tasks with high performance, the features that make it stand out are advanced reasoning, math, and coding. DeepSeek R1 can successfully handle complex reasoning tasks thanks to MoE and Multi-Head Latent Attention (MLA) technologies.

DeepSeek R1 Pricing

If you want to experience the DeepSeek R1 model only as an AI chatbot, you can try it for free on DeepSeek's official website. However, if you want to use DeepSeek R1 as an API, you need to pay the following pricing. 

  • Input Cache Hit: $0.14 per million tokens  
  • Input Cache Miss: $0.55 per million tokens  
  • Output Price: $2.19 per million tokens  
DeepSeek R1 Pricing

How to Access DeepSeek R1?

To access the DeepSeek R1 model only as an AI chatbot interface, you can visit the DeepSeek official website. If you want to install the DeepSeek R1 model as an API, you can get it from GitHub or DeepSeek.

How to Access DeepSeek R1?

If you want to integrate the DeepSeek R1 model directly into your workflow, you can access it on TextCortex.

TextCortex offers multiple LLMs, including the DeepSeek R1 model, to help users automate complex workflows, lighten their workload, and save time. You can leverage the DeepSeek R1 model for your knowledge management tasks, documentation creation, web-driven research tasks, data analysis tasks, and coding and math needs via TextCortex.

DeepSeek R1 vs. OpenAI-o1

DeepSeek R1 model scores similarly to OpenAI’s most advanced model o1 in benchmarks designed to measure the performance of LLMs. Both large language models offer advantages and disadvantages over one another. If you’re wondering about the differences and similarities between DeepSeek R1 and OpenAI-o1 models and aren’t sure which model to use, we’ve got you covered!

Performance & Benchmarks

DeepSeek R1 model has similar scores to OpenAI-o1 in benchmarks designed to measure the performance and capabilities of large language models. When it comes to the natural language processing performance of the two LLMs, OpenAI-o1 has slightly better results. However, in math and coding benchmarks, the DeepSeek R1 model managed to slightly outperform OpenAI-o1. Since there are small differences in the benchmark performance between the two large language models, both can help you complete complex tasks.

DeepSeek R1 vs. OpenAI Performance

OpenAI-o1 vs. DeepSeek R1: Pricing

Both OpenAI-o1 and DeepSeek R1 models may leave users confused about which to choose, with similar performance in benchmarks. However, the input and output pricing offered by the two large language models may make your choice a little easier. The OpenAI-o1 model charges between $7.50 and $15 for every 1 million input tokens, and $60 for every 1 million output tokens.

OpenAI-o1 vs. DeepSeek R1: Pricing

On the other hand, the DeepSeek R1 model charges between $0.14 and $0.55 per 1 million input tokens and $2.19 per 1 million output tokens. Considering the huge price difference between the two large language models and their almost equal performance, the DeepSeek R1 model is a more budget-friendly option.

Use Cases

Since its development, the OpenAI-o1 model has been used in natural language, coding, reasoning, data analysis, and math tasks to power different AI tools. You can choose the OpenAI-o1 model to perform any task in your organization without thinking.

On the other hand, the DeepSeek R1 model is designed to provide higher performance in advanced reasoning and coding tasks thanks to its MoE technology and 671 billion parameters. Although the OpenAI-o1 model also has high performance in coding and reasoning tasks, the DeepSeek R1 model stands out as a more cost-effective alternative.

A Better Alternative: TextCortex

If you have areas in your enterprise and organization where you can use both OpenAI-o1 and DeepSeek R1 models and you are not sure which one to choose, you can integrate both into your business workflow through TextCortex. TextCortex is an AI assistant designed to automate complex tasks by integrating into the workflow of its users. It offers multiple LLMs such as OpenAI-o1, Claude 3.5 Sonnet, DeepSeek R1, multiple AI image generators, web search, knowledge bases, powerful RAG (Retrieval-augmented generation) and 30,000+ website and app integrations.

TextCortex is an ideal choice not only for automating complex tasks of your organization but also for increasing the individual performance of your employees. Using TextCortex, your employees can quickly access what they are looking for in your internal data and complete it without losing focus on the task at hand. Check out the results from one of our case studies:

  • TextCortex was implemented for Kemény Boehme Consultants as a solution to tackle these challenges and today employees report increased efficiency and productivity (saving 3 work days per month per employee on average).
  • AICX, an ecosystem partner of TextCortex, was integral to the onboarding and helped achieve a 70% activation rate of the team within the first weeks.
  • Employee confidence in using and working with AI increased by 60%.‍
  • The implementation results in a 28x return on investment (ROI).

Frequently Asked Questions

Is DeepSeek a Chinese company?

DeepSeek was founded in 2023 by Liang Wenfeng in Hangzhou, China. The DeepSeek model was developed using Nvidia’s A100 chips. Even after Nvidia’s A100 chip ban, the DeepSeek continued to be developed, and on January 20, 2025, the DeepSeek R1 model, which competes with the performance of the OpenAI-o1 model, was announced.

What does DeepSeek R1 do?

DeepSeek R1 can perform basic tasks that a large language model can do, such as code generation, problem-solving, content generation, translation, paraphrasing, and data analysis. Tasks that DeepSeek R1 shines in include coding and reasoning. DeepSeek R1 can generate more accurate results by breaking down complex reasoning tasks into smaller steps with MoE and Multi-Head Latent Attention (MLA) technologies.

What is so special about DeepSeek?

The DeepSeek R1 model offers advanced reasoning, math, and problem-solving capabilities to its users. What makes it so special is that it offers performance equal to the OpenAI-o1 model at a much lower cost. Generating 1 million tokens of output with the DeepSeek R1 model costs $2.19.