How to run DeepSeek-R1 in production

With benchmarks rivaling OpenAI’s o1 model at a significantly lower cost to run, DeepSeek has transformed the AI landscape, challenging the notion that training massive models is the key to disruptive AI products.

But deploying it is far from straightforward.

In this webinar, we'll break down what makes DeepSeek so impressive, why it's difficult to run, and how to overcome these difficulties to get a dedicated and secure DeepSeek-R1 deployment. Specifically, we'll cover:

1. The rise of DeepSeek: Why DeepSeek is a game-changer for LLM applications.

2. Why running DeepSeek-R1 in production is hard: From H200 GPU availability to running multi-node inference, we'll break down why running DeepSeek isn't easy from a capacity or scaling standpoint.

3. How to get a dedicated deployment of DeepSeek-R1: Learn what it takes to run DeepSeek-R1 in a dedicated and self-serve way, including self-hosting in your own VPC.

4. Live demo: See DeepSeek in action and learn how businesses in healthcare, finance, and SaaS use DeepSeek for agentic applications, transcription, and more.

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