AWS LLM Deployment: SageMaker vLLM vs. Bedrock for Open Models

Deploying open-source Large Language Models (LLMs) on AWS presents complexities beyond initial setup, particularly concerning infrastructure ownership and performance scaling. The article contrasts two AWS approaches: Amazon SageMaker with vLLM for greater control over the serving layer, and Amazon Bedrock for a more managed experience. The SageMaker with vLLM method offers fine-grained control over compute, inference engines, and configurations, making it suitable for applications where model and inference performance are critical. However, this control necessitates managing aspects like GPU utilization, memory, batching, and scaling, which can be challenging to troubleshoot. AI

IMPACT Provides guidance on managing LLM infrastructure costs and performance on cloud platforms.

RANK_REASON The article discusses practical implementation details and comparisons of cloud services for deploying existing LLMs, rather than a new model release or research breakthrough.

Read on dev.to — LLM tag →

• Amazon Bedrock
• Amazon SageMaker
• Apache Spark
• AWS
• boto3
• graphics processing unit
• OpenAI
• Open LLM
• vLLM

• infra
• product

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