DeepSeek R1 on SageMaker vs. Bedrock: What's the Difference?

 

DeepSeek R1 on SageMaker vs. Bedrock: What's the Difference?

DeepSeek R1 is an open-source AI model that can be deployed in different ways on AWS, but should you use SageMaker or Bedrock? The choice depends on whether you need to train/customize R1 or simply use it as a pre-trained model.

In this post, we'll cut through the confusion and clearly outline what each AWS service can and cannot do with DeepSeek R1.

SageMaker vs. Bedrock: The Quick Answer

Feature	SageMaker	Bedrock
Can you train or fine-tune DeepSeek R1?	✅ Yes	❌ No
Can you host and serve DeepSeek R1?	✅ Yes (via Endpoints)	✅ Yes (if AWS adds R1 to Bedrock, but not currently available)
Do you have full model control?	✅ Yes	❌ No (pre-trained models only)
Do you need to manage infrastructure?	✅ Yes (CPU/GPU selection, scaling, etc.)	❌ No (AWS fully manages it)
Best for…	Training, fine-tuning, and custom AI workloads	Quickly deploying pre-trained AI with minimal setup

When to Use SageMaker for DeepSeek R1

Use SageMaker when you need:

✔ To train or fine-tune R1 with your own data.

✔ Full control over the model, including infrastructure, optimization, and scaling.

✔ To host and deploy a fine-tuned version of R1 for real-time inference.

🔹 Example Use Case: A company wants to fine-tune DeepSeek R1 with their proprietary data for a custom chatbot. They train the model in SageMaker and then deploy it using SageMaker Endpoints.

When to Use Bedrock for DeepSeek R1 (If Supported in the Future)

Use Bedrock when you need:

✔ A fully managed, pre-trained model—no training or infrastructure setup.

✔ To quickly build AI apps without dealing with GPUs or fine-tuning.

✔ A simple API for AI inference that scales automatically.

🔹 Example Use Case: A startup wants to build a chatbot but doesn’t need custom training. If DeepSeek R1 were available on Bedrock, they could simply call an API and get responses without managing a model.

Final Thoughts

💡 SageMaker = Custom AI Development (Train, Fine-Tune, Deploy).

💡 Bedrock = Pre-Trained AI APIs (Use Out-of-the-Box Models).

Right now, if you want to use DeepSeek R1 on AWS, SageMaker is your only option. If AWS ever adds DeepSeek R1 to Bedrock, then it will become a faster, easier choice for those who just want pre-trained AI without customization. 🚀

Need DeepSeek/AWS Expertise?

If you're looking for guidance on DeepSeek/AWS challenges or want to collaborate, feel free to reach out! We'd love to help you tackle your DeepSeek/AWS projects. 🚀

Email us at: info@pacificw.com

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