How to beginner · 3 min read

How to run Llama 3 8B locally

Q: How to run Llama 3 8B locally

Use Ollama to run Llama 3 8B locally by installing the Ollama CLI, pulling the model, and running it via CLI or Python SDK. Ollama handles model hosting and inference on your machine without cloud dependencies.

Quick answer

Use Ollama to run Llama 3 8B locally by installing the Ollama CLI, pulling the model, and running it via CLI or Python SDK. Ollama handles model hosting and inference on your machine without cloud dependencies.

PREREQUISITES

macOS or Linux (x86_64 or ARM64)
Ollama CLI installed (https://ollama.com/docs/install)
Python 3.8+
pip install ollama

Setup Ollama CLI

Install the Ollama CLI to manage and run local AI models. Visit Ollama installation guide for platform-specific instructions.

On macOS, you can install via Homebrew:

bash

brew install ollama

Run Llama 3 8B locally via CLI

Pull the llama-3-8b model and run it locally using Ollama CLI commands.

bash

ollama pull llama-3-8b
ollama run llama-3-8b --prompt "Hello, Llama 3!"

output

Llama 3 8B response: Hello, Llama 3! How can I assist you today?

Run Llama 3 8B locally with Python

Use the ollama Python package to interact with Llama 3 8B programmatically.

python

import ollama

response = ollama.chat(
    model="llama-3-8b",
    messages=[{"role": "user", "content": "Hello, Llama 3!"}]
)
print(response.text)

output

Hello, Llama 3! How can I assist you today?

Common variations

Use different prompts or system messages to customize responses.
Run other Llama 3 variants by changing the model name (e.g., llama-3-13b).
Use Ollama's streaming API for real-time token generation.

Troubleshooting

If ollama run fails, ensure the model is fully downloaded with ollama pull llama-3-8b.
Check your system architecture compatibility (x86_64 or ARM64).
Restart the Ollama daemon if responses hang: ollama restart.

✅

Key Takeaways

Install Ollama CLI to manage local Llama 3 models easily.
Run Llama 3 8B locally via CLI or Python SDK for flexible integration.
Ensure your system architecture and Ollama daemon are properly configured.
Use Ollama's streaming and model variants for advanced use cases.

Verified 2026-04 · llama-3-8b

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