Downloading Models
The llama CLI tool helps you setup and use the Llama Stack. It should be available on your path after installing the llama-stack package.
Installation
You have two ways to install Llama Stack:
-
Install as a package: You can install the repository directly from PyPI by running the following command:
pip install llama-stack -
Install from source: If you prefer to install from the source code, follow these steps:
mkdir -p ~/local
cd ~/local
git clone git@github.com:meta-llama/llama-stack.git
uv venv myenv --python 3.12
source myenv/bin/activate # On Windows: myenv\Scripts\activate
cd llama-stack
pip install -e .
Downloading models via CLI
You first need to have models downloaded locally.
To download any model you need the Model Descriptor. This can be obtained by running the command
llama model list
You should see a table like this:
+----------------------------------+------------------------------------------+----------------+
| Model Descriptor(ID) | Hugging Face Repo | Context Length |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-8B | meta-llama/Llama-3.1-8B | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-70B | meta-llama/Llama-3.1-70B | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-405B:bf16-mp8 | meta-llama/Llama-3.1-405B | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-405B | meta-llama/Llama-3.1-405B-FP8 | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-405B:bf16-mp16 | meta-llama/Llama-3.1-405B | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-8B-Instruct | meta-llama/Llama-3.1-8B-Instruct | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-70B-Instruct | meta-llama/Llama-3.1-70B-Instruct | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-405B-Instruct:bf16-mp8 | meta-llama/Llama-3.1-405B-Instruct | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-405B-Instruct | meta-llama/Llama-3.1-405B-Instruct-FP8 | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.1-405B-Instruct:bf16-mp16 | meta-llama/Llama-3.1-405B-Instruct | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-1B | meta-llama/Llama-3.2-1B | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-3B | meta-llama/Llama-3.2-3B | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-11B-Vision | meta-llama/Llama-3.2-11B-Vision | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-90B-Vision | meta-llama/Llama-3.2-90B-Vision | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-1B-Instruct | meta-llama/Llama-3.2-1B-Instruct | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-3B-Instruct | meta-llama/Llama-3.2-3B-Instruct | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-11B-Vision-Instruct | meta-llama/Llama-3.2-11B-Vision-Instruct | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama3.2-90B-Vision-Instruct | meta-llama/Llama-3.2-90B-Vision-Instruct | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama-Guard-3-11B-Vision | meta-llama/Llama-Guard-3-11B-Vision | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama-Guard-3-1B:int4-mp1 | meta-llama/Llama-Guard-3-1B-INT4 | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama-Guard-3-1B | meta-llama/Llama-Guard-3-1B | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama-Guard-3-8B | meta-llama/Llama-Guard-3-8B | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama-Guard-3-8B:int8-mp1 | meta-llama/Llama-Guard-3-8B-INT8 | 128K |
+----------------------------------+------------------------------------------+----------------+
| Prompt-Guard-86M | meta-llama/Prompt-Guard-86M | 128K |
+----------------------------------+------------------------------------------+----------------+
| Llama-Guard-2-8B | meta-llama/Llama-Guard-2-8B | 4K |
+----------------------------------+------------------------------------------+----------------+
To download models, you can use the llama download command.
Downloading from Meta
Here is an example download command to get the 3B-Instruct/11B-Vision-Instruct model. You will need META_URL which can be obtained from here. Note: You need to quote the META_URL
Download the required checkpoints using the following commands:
# download the 8B model, this can be run on a single GPU
llama download --source meta --model-id Llama3.2-3B-Instruct --meta-url 'META_URL'
# you can also get the 70B model, this will require 8 GPUs however
llama download --source meta --model-id Llama3.2-11B-Vision-Instruct --meta-url 'META_URL'
# llama-agents have safety enabled by default. For this, you will need
# safety models -- Llama-Guard and Prompt-Guard
llama download --source meta --model-id Prompt-Guard-86M --meta-url 'META_URL'
llama download --source meta --model-id Llama-Guard-3-1B --meta-url 'META_URL'
Downloading from Hugging Face
Essentially, the same commands above work, just replace --source meta with --source huggingface.
llama download --source huggingface --model-id Llama3.1-8B-Instruct --hf-token <HF_TOKEN>
llama download --source huggingface --model-id Llama3.1-70B-Instruct --hf-token <HF_TOKEN>
llama download --source huggingface --model-id Llama-Guard-3-1B --ignore-patterns *original*
llama download --source huggingface --model-id Prompt-Guard-86M --ignore-patterns *original*
Important: Set your environment variable HF_TOKEN or pass in --hf-token to the command to validate your access. You can find your token at https://huggingface.co/settings/tokens.
Default for `llama download` is to run with `--ignore-patterns *.safetensors` since we use the `.pth` files in the `original` folder. For Llama Guard and Prompt Guard, however, we need safetensors. Hence, please run with `--ignore-patterns original` so that safetensors are downloaded and `.pth` files are ignored.
List the downloaded models
To list the downloaded models with the following command:
llama model list --downloaded
You should see a table like this:
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓
┃ Model ┃ Size ┃ Modified Time ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩
│ Llama3.2-1B-Instruct:int4-qlora-eo8 │ 1.53 GB │ 2025-02-26 11:22:28 │
├─────────────────────────────────────────┼──────────┼─────────────────────┤
│ Llama3.2-1B │ 2.31 GB │ 2025-02-18 21:48:52 │
├─────────────────────────────────────────┼──────────┼─────────────────────┤
│ Prompt-Guard-86M │ 0.02 GB │ 2025-02-26 11:29:28 │
├─────────────────────────────────────────┼──────────┼─────────────────────┤
│ Llama3.2-3B-Instruct:int4-spinquant-eo8 │ 3.69 GB │ 2025-02-26 11:37:41 │
├─────────────────────────────────────────┼──────────┼─────────────────────┤
│ Llama3.2-3B │ 5.99 GB │ 2025-02-18 21:51:26 │
├─────────────────────────────────────────┼──────────┼─────────────────────┤
│ Llama3.1-8B │ 14.97 GB │ 2025-02-16 10:36:37 │
├─────────────────────────────────────────┼──────────┼─────────────────────┤
│ Llama3.2-1B-Instruct:int4-spinquant-eo8 │ 1.51 GB │ 2025-02-26 11:35:02 │
├─────────────────────────────────────────┼──────────┼─────────────────────┤
│ Llama-Guard-3-1B │ 2.80 GB │ 2025-02-26 11:20:46 │
├─────────────────────────────────────────┼──────────┼─────────────────────┤
│ Llama-Guard-3-1B:int4 │ 0.43 GB │ 2025-02-26 11:33:33 │
└─────────────────────────────────────────┴──────────┴─────────────────────┘