There are two main options to run DeepSeek R1 locally on your computer:

1. LLM Studio:

   • LLM Studio is an easy-to-use application that you can download for Mac, Windows, or Linux.
   • In the app, you can start a new chat and choose the DeepSeek R1 model from the available options.
   • You can also add other open-source language models like Llama 3.3, GPT-2, and more to compare their outputs.
   • LLM Studio provides a simple and intuitive interface for interacting with the local language models.

2. Anthropic's AMA Platform:

   • Anthropic's AMA platform allows you to download and run various open-source language models, including DeepSeek R1, on your local machine.
   • This option is more technical but provides more flexibility. You can choose different versions of DeepSeek R1, such as the 32B or 7B models, depending on your computer's capabilities.
   • With AMA, you can run multiple models simultaneously and compare their outputs side-by-side.
   • AMA also allows you to upload your own files and interact with them using the installed language models.

Both options enable you to use DeepSeek R1 without relying on the DeepSeek website, providing more control and privacy. The LLM Studio approach is more beginner-friendly, while the AMA platform offers more advanced features and customization options.

Perplexity AI is another platform that offers access to the DeepSeek R1 model. This version of DeepSeek R1 is hosted in the US by Perplexity, making it available to free users.

Perplexity's implementation of DeepSeek R1 combines search capabilities with the model's reasoning abilities. When you ask a question, Perplexity breaks it down into smaller sub-questions and searches across multiple web sources, in addition to using the R1 model's knowledge base.

This approach often results in comprehensive and well-researched answers. The free plan provides access to the R1 reasoning model, while the paid Pro plan unlocks additional features like deeper research capabilities and expanded web source access.

Perplexity with DeepSeek R1 is well-suited for tasks that require research and analysis, as the combination of search and reasoning can provide insightful and informative responses. However, if you don't need the search functionality, you may want to consider other options for using DeepSeek R1 that are more focused on the reasoning capabilities alone.

One of the ways to use Deep Seek R1 without the website is through the Monica platform. Monica is an all-in-one platform that provides access to a variety of top AI models, including Deep Seek R1, ChatGPT, Whisper, and various image and video generation models.

The key benefits of using Monica are:

1. Single Access Point: With Monica, you don't have to sign up for multiple individual apps to access different AI models. Everything is available in one place.

2. Chrome Extension Integration: Monica offers a Chrome extension that allows you to access the AI models directly from your web browser, making it easy to use across different websites and applications.

3. Multimodal Capabilities: In addition to language models like Deep Seek R1, Monica also provides access to image and video generation models, enabling you to work with various content types.

4. Flexible Model Selection: When interacting with the AI models, you can choose which specific model you want to use, including the option to combine models that don't have web access with those that do.

5. Web Page Interaction: The Monica Chrome extension allows you to interact with web pages directly, providing summaries, key points, and the ability to ask follow-up questions.

Overall, Monica offers a convenient and comprehensive way to access a wide range of AI models, including Deep Seek R1, without the need to navigate multiple platforms or sign up for individual services.

Grok with a Q is a platform that provides access to open-source models like Deep Seek R1. One of the key advantages of using Grok with a Q is the speed at which it processes tasks.

In the example provided, the author gives Grok with a Q a coding task, and the response is generated in just a matter of seconds. The platform shows the speed of the response, which is 27 tokens per second. This is significantly faster than other chat interfaces that use Deep Seek R1.

The author notes that the speed of Grok with a Q is 5 to 10 times faster than some of the other platforms that offer access to Deep Seek R1. This makes Grok with a Q an excellent choice for users who require quick responses, especially for tasks that involve coding or other technical applications.

Overall, the speed advantage of Grok with a Q is a compelling reason to consider using this platform for your Deep Seek R1 needs.

Nvidia Nim is a powerful platform that allows you to leverage various AI models, including DeepSeek R1. One of the key advantages of using Nvidia Nim for DeepSeek R1 is the ability to customize the model's behavior through adjustable parameters.

When you access DeepSeek R1 on the Nvidia Nim platform, you'll find the "Parameters" section, which provides you with the ability to fine-tune the model's response. One of the most notable parameters is the "Temperature," which allows you to control the model's creativity and adherence to the prompt.

By adjusting the temperature, you can find the right balance between following the prompt exactly and allowing the model to generate more creative and diverse responses. Setting the temperature closer to 0 will result in the model closely following the prompt, while increasing the temperature towards 1 will encourage more exploratory and imaginative responses.

In addition to the temperature parameter, Nvidia Nim offers a range of other customization options that you can explore to tailor the DeepSeek R1 model to your specific needs. These include parameters related to the model's sampling, top-k/top-p filtering, and other advanced settings.

By leveraging the customization capabilities of Nvidia Nim, you can unlock the full potential of DeepSeek R1 and optimize its performance for your specific use cases, whether it's for technical applications, open-source customizations, or any other task that requires the model's reasoning capabilities.