DeepSeek
Interest in DeepSeek LLM
Differences between DeepSeek V3 and DeepSeek R1
In addition to MoE and MLA, DeepSeek R1 implements a multitoken prediction architecture first introduced by Meta. Instead of just predicting the next word each time the model is executed, DeepSeek R1 predicts the next two tokens in parallel.
Minimum requirements to run DeepSeek model locally
There are distilled versions of the model starting at 1.5 billion parameters, going all the way up to 70 billion parameters. These distilled models are able to run on consumer-grade hardware. Therefore, the lower the parameters, the less resources are required and the higher the parameters, the more resources are required.
DeepSeek vs other LLMs
Finally, its CoT approach is verbose, revealing more of the nuances involved in how LLMs respond to prompts compared with other reasoning models. The latest models from OpenAI (o3) and Google (Gemini 2.0 Flash Thinking) reveal additional reasoning to the end user, though in a less verbose fashion.
A frontier model refers to the most advanced LLMs available that include complex reasoning and problem-solving capabilities. Currently, OpenAI’s o1 and o3 models along with DeepSeek R1 are the only frontier models available.
Deploying the open-source version of DeepSeek on a system is likely safer to use versus DeepSeek’s website or mobile applications, since it does not require a connection to the internet to function.
Concerns surrounding using DeepSeek’s website and mobile applications
DeepSeek’s ban
This article is contributed by the Tenable Security Response Team.
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