---
title: "Discussion on \"Running Ollama Locally vs in the Cloud: A Practical Look at AI Infrastructure\" | Hashnode"
description: "Discussion on \"Running Ollama Locally vs in the Cloud: A Practical Look at AI Infrastructure\". A real-world reflection on testing a local machine learning model with Ollama on a personal Windows 11 notebook, and why cloud environments still matter for companies that need speed, scale, and reliability."
url: "https://hashnode.com/posts/running-ollama-locally-vs-in-the-cloud-a-practical-look-at-ai-infrastructure/6a2a848ba339b335c15e1f38"
---

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# [Running Ollama Locally vs in the Cloud: A Practical Look at AI Infrastructure](https://claudiosantos.hashnode.dev/running-ollama-locally-vs-in-the-cloud-a-practical-look-at-ai-infrastructure?utm_source=hashnode&utm_medium=feed)

A real-world reflection on testing a local machine learning model with Ollama on a personal Windows 11 notebook, and why cloud environments still matter for companies that need speed, scale, and reliability.

Jun 11 · 9 min read · claudiosantos.hashnode.dev  
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-   [#ai](https://hashnode.com/tag/ai)
-   [#machine-learning](https://hashnode.com/tag/machine-learning)
-   [#ollama](https://hashnode.com/tag/ollama)
-   [#cloud-computing](https://hashnode.com/tag/cloud-computing)
-   [#mlops](https://hashnode.com/tag/mlops)

## Written by

[Claudio Santos](https://hashnode.com/@claudiosantos)

@claudiosantos · Belo Horizonte, Brazil

  
[View profile](https://hashnode.com/@claudiosantos)

Exploring Cloud Intelligence through practice and continuous Learning

I’m an IT Support and NOC professional focused on monitoring, incident response, and Microsoft cloud environments. I’m transitioning into Cloud and AI, learning through hands on practice in AWS and Azure while sharing practical insights about Cloud Intelligence, automation, and modern infrastructure. Certified AZ 900 and AI 900, continuously learning and improving through real world experience.

## Responses 2

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[Mateo Ruiz](https://hashnode.com/@mateoruiz)

[Jun 11](https://hashnode.com/posts/running-ollama-locally-vs-in-the-cloud-a-practical-look-at-ai-infrastructure/6a2a848ba339b335c15e1f38/comment/6a2a85863b020503009c35db)

I like that this post doesn't turn it into a local-vs-cloud debate. They're really different stages of the same journey.

Running Ollama locally is one of the fastest ways to understand what AI workloads actually cost in terms of memory, compute, and latency. A lot of those realities are hidden when you're only consuming APIs.

What I've seen in practice is that local models are great for experimentation, internal tools, and privacy-sensitive workflows, while cloud infrastructure becomes important once reliability, concurrency, and operational support matter. Most teams will probably end up with some hybrid mix rather than choosing one side forever.

The best lesson from running models locally isn't saving API costs it's learning what your future production architecture will eventually have to handle.

[Claudio Santos](https://hashnode.com/@claudiosantos)

[Jun 11](https://hashnode.com/posts/running-ollama-locally-vs-in-the-cloud-a-practical-look-at-ai-infrastructure/6a2a848ba339b335c15e1f38/comment/6a2a85863b020503009c35db#reply-6a2a877b89cdb2328be981d3)

Hi Mateo, thank you so much for your thoughtful comment.

I completely agree with your point. Local AI and cloud AI should not be treated as opposite sides, but as parts of the same learning and implementation journey. Running models locally helps us understand the real impact of memory, compute, and latency, while the cloud shows how these workloads behave when scalability, reliability, and production support become necessary.

Your view about a hybrid approach makes a lot of sense. In practice, that will probably be the most realistic path for many teams.

Really appreciate you sharing this perspective.