If you are looking for an LLM that offers similar performance to the OpenAI-o1 large language model but is much cheaper, look no further than DeepSeek R1. DeepSeek R1 is a fully open-source LLM licensed by MIT (Massachusetts Institute of Technology). The DeepSeek R1 model comes in two different versions, 70b and 32b. If you are looking for a high-performance LLM alternative to the OpenAI-o1 model, we recommend that you put the DeepSeek R1 model on your radar.
In this article, we will examine the DeepSeek R1 model and explore its features.
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TL; DR
- DeepSeek-R1 is a large language model developed and published by the Chinese startup DeepSeek that has almost equal performance to the OpenAO-o1 model.
- You can access the DeepSeek R1 model via the DeepSeek official website or GitHub.
- The DeepSeek R1 model has a much lower pricing policy than its competitor, the OpenAI-o1 model.
- The DeepSeek R1 model scores close to the OpenAI-o1 model in most benchmarks in terms of natural language, math, reasoning, and coding performance, and outperforms it in some.
- If you need an AI assistant that can integrate multiple LLMs, such as OpenAI-o1, DeepSeek R1, and Claude 3.5 Sonnet, into your organization and increase its overall efficiency, TextCortexis the way to go.
What is DeepSeek R1?
The DeepSeek R1 model is a large language model developed to perform complex reasoning, mathematical problem-solving and programming tasks. The DeepSeek R1 model generates output by using its parameters constructed with the Mixture of Experts (MoE) approach with maximum efficiency. DeepSeek R1 model comes in two different versions, 70b and 32b, depending on the usage areas and needs.

How to Access DeepSeek R1?
If you want to access the DeepSeek R1 model as an AI chatbot, simply head to the DeepSeek official website and click the “Start Now” button. You will then be directed to an AI chatbot web interface where you can access the DeepSeek R1 model with limited access.

If you want to use the DeepSeek R1 model as an API, you can install it via DeepSeek's official website or install it via GitHub.
Using DeepSeek R1 via TextCortex
The innovative and alternative method to access the DeepSeek R1 model is to experience it through TextCortex. TextCortex has a multiple LLMs library including OpenAI-o1, GPT-4o, and Claude 3.5 Sonnet to provide the best service and task-oriented solutions to its users. One of the latest members of this library is the DeepSeek R1 model. If you are looking for a method to integrate the DeepSeek R1 model directly into your workflow, TextCortex is your savior. To use the DeepSeek R1 model via TextCortex, all you need to do is select the DeepSeek R1 model from ZenoChat's chat settings.
DeepSeek R1 Pricing
You can use the DeepSeek R1 model as an AI chatbot for free via its official website. If you use the DeepSeek R1 model as API, you will be charged as follows.
- Input Cache Hit Price: $0.14 / 1M Tokens
- Input Cache Miss Price: $0.55 / 1M Tokens
- Output Price: $2.19 / 1M Tokens

DeepSeek R1 Features
Although the DeepSeek R1 model has a lower price tag than advanced LLMs like OpenAI-o1, it does not lag behind them in performance. The DeepSeek R1 model can easily handle advanced reasoning and coding tasks with both its architecture and its performance in benchmarks. Let’s take a closer look at the features of DeepSeek R1.
DeepSeek R1 Architecture
The architecture of the DeepSeek R1 model was developed to balance performance and efficiency. Here are the model specifications:
- Total Parameters: 671 Billion
- Active Parameters per Token: 37 billion
- Training Data: 14.8 trillion tokens
- Context Window: 128K Tokens
The DeepSeek R1 model uses the Mixture of Experts (MoE), Multi-head Latent Attention (MLA), and Multi-Token Prediction (MTP) approach while training and generating output. This approach ensures that the model gives the best result with minimum error and cost.
DeepSeek R1 Performance
Despite its low pricing policy, the DeepSeek R1 model is an LLM with a performance that competes with the OpenAI-o1 model. When it comes to the natural language capabilities of DeepSeek R1, it managed to reach a score of 90.8 in the MMLU (Measuring Massive Multitask Language Understanding) benchmark. According to the same benchmark, the OpenAI-o1 model has a score of 91.8, and the OpenAI-o1 mini model has a score of 88.5.

When it comes to DeepSeek R1’s reasoning and coding performance, it has a score of 96.3 in the Codeforce benchmark, 71.5 in the GPQA-diamond benchmark, and 97.3 in the MATH-500 benchmark. The DeepSeek R1 model, which comes very close to the OpenAI-o1 model with its performance in the Codeforce and GPQA-diamond benchmarks, managed to outperform the OpenAI-o1 model in the MATH-500 benchmark.
DeepSeek R1 Reasoning and Coding
Although the DeepSeek R1 model is successful in handling natural language processing tasks, the tasks it shines in are reasoning and coding. The DeepSeek R1 model offers its users high efficiency in solving complex mathematical problems.

The DeepSeek R1 model can be considered a budget-friendly but high-performance option for coding tasks with its performance in coding benchmarks. It has almost equal scores with the OpenAI-o1 model in coding benchmarks. In addition, the model demonstrates an ability to break down problems into smaller steps using chain-of-thought reasoning.
TextCortex
If you are looking for a company AI assistant powered by advanced LLMs such as OpenAI-o1, Claude 3.5 Sonnet and DeepSeek R1 then TextCortex is designed for you.

TextCortex offers features such as multiple LLMs, multiple image generators, web search, knowledge bases, powerful RAG, and writing assistance to automate complex workflows and boost knowledge management games for its users. With TextCortex, you can save time by automating both your professional and personal tasks.
TextCortex not only helps organizations ease their professional workload but also helps you increase the individual performance of your employees. Using ZenoChat, a conversational AI assistant developed by TextCortex, you can provide all your employees with quick access to data in your knowledge base and provide them with a multi-functional AI assistant. 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-R1 free?
Although the DeepSeek R1 model is free to use as an AI chatbot, if you want to use it as an API, you need to pay $0.14 per million tokens for input cache hits, $0.55 per million tokens for input cache misses, and $2.19 per million output tokens.
What is DeepSeek-R1?
The DeepSeek-R1 model is a large language model that offers high coding, reasoning, math, and natural language performance that you can use as a cost-efficient alternative to the OpenAI-o1 model. You can use the DeepSeek-R1 model as an AI chatbot and complete your tasks in a conversational format with it, or you can integrate it into your applications as an API. For example, you can create a DeepSeek-R1-powered AI agent by integrating the DeepSeek-R1 API into AI agent builders such as AutoGen.
Is DeepSeek-R1 Chinese?
DeepSeek is an MIT-licensed LLM developed by a Chinese startup that offers performance that rivals the R1 model and the OpenAI-o1 model. The DeepSeek-R1 model offers almost equal performance to the OpenAI-o1 model at a much lower price.