# AWS shows how to deploy decision models with llama.cpp on SageMaker AI

Digest AI · Enterprise & Industry · published 2026-10-12T15:51:46Z

Canonical: https://digestai.news/story/aws-shows-how-to-deploy-decision-models-with-llama-cpp-on-sagemaker-ai

## Summary

AWS published a tutorial on deploying decision models using llama.cpp on Amazon SageMaker AI. The post demonstrates two deployment paths from the same GGUF model: a standard text-generation path serving OpenAI-compatible chat completions, and a structured-decision path using a SemIf adapter that returns probabilities over declared options instead of generated text. The structured-decision path builds a child container image via AWS CodeBuild and stores it in Amazon ECR, replacing the default server entry point with a SageMaker-compatible adapter. The sample uses a 4B Q4KM model as its quality-first default after smaller 2B and 0.8B models achieved 66.7% and 58.4% accuracy. The tutorial includes CPU and GPU deployment options, instance pool configuration for GPU fallback, and cleanup steps.

## Key points

- AWS tutorial deploys llama.cpp decision models on SageMaker AI with two paths
- SemIf adapter returns option probabilities instead of generated text

## Why it matters

Shows enterprises how to serve structured decision models on managed infrastructure, enabling routing, policy checks, and agent action selection without parsing generated prose.

## Sources

1. [Deploy decision models with llama.cpp on Amazon SageMaker AI](https://aws.amazon.com/blogs/machine-learning/deploy-decision-models-with-llama-cpp-on-amazon-sagemaker-ai) (AWS Machine Learning Blog, 2026-10-12, primary source)

Part of the developing story: [The AI Model Format Evolution Saga](https://digestai.news/thread/qwen3-8-27b-gguf-updated-with-new-tensor-layout) (6 stories)

## Cite

Digest AI, "AWS shows how to deploy decision models with llama.cpp on SageMaker AI", 12 October 2026, https://digestai.news/story/aws-shows-how-to-deploy-decision-models-with-llama-cpp-on-sagemaker-ai

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