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Download Llama 3.2

12 Dec 20244 min read

Download Llama

Excerpt

The open source AI model you can fine-tune, distill and deploy anywhere. Our latest models are available in 8B, 70B, and 405B variants.

You are all set!

Request ID: 427160947061876

Requested models:

  • Llama 3.2 1B
  • Llama 3.2 3B
  • Llama Guard 3 1B
  • Llama Guard 3 1B INT4
  • Llama 3.1 8B
  • Llama 3.1 70B
  • Llama 3.1 405B
  • Llama Guard 3 8B
  • Prompt Guard
  • Llama 3
  • Llama 2

The models listed below are now available to you as a commercial license holder. By downloading a model, you are agreeing to the terms and conditions of the

License

,

Acceptable Use Policy

and Meta’s

privacy policy

.

How to download the model

Visit the Llama repository in GitHub where instructions can be found in the Llama README

Install the Llama CLI

In your preferred environment run the command below

Find models list

See latest available models by running the following command and determine the model ID you wish to download:

If you want older versions of models, run the command below to show all the available Llama models:

Select a model

Select a desired model by running:

Specify custom URL

Llama 3.1: 405B, 70B & 8B

When the script asks for your unique custom URL, please paste the URL below

https://llama3-2-lightweight.llamameta.net/*?Policy=eyJTdGF0ZW1lbnQiOlt7InVuaXF1ZV9oYXNoIjoiNjA3M3RmZ2VrZHc2emVlcnk2cTZ6NnllIiwiUmVzb3VyY2UiOiJodHRwczpcL1wvbGxhbWEzLTItbGlnaHR3ZWlnaHQubGxhbWFtZXRhLm5ldFwvKiIsIkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTcyODE0MDkxMX19fV19&Signature=D0CrJUe7rQnJUlG4gg9PjjsJKiG%7E4mP%7Ecg6ZuzbSqRhI7ToydNilNiobGtUFrQKk1Xu8C-HhZVnweVpcuJq1duJxx%7Eb9fnBqQiN9zVnajvtkODRpRrRxIocBXqi8xgoBcNCWZhJ8UqnYE4IW6uMpBhbp91TwZnpNK6W85gU3qhix4R-2K%7EdqC69%7EOop8avOiD%7EPN1TIp5hd4jxbSQhoAo8KvW033rlEWUkhT5GDIeXPcXV32tUHecxOumhqZIsAgN7ReonaOF9lkXmHbOWLLORpd2aFD95JOM-Qm3WSyR2x-ox3v72Rh4IMLOvlYfO-ArcSB1do5-LuYwkAg4lKBpg__&Key-Pair-Id=K15QRJLYKIFSLZ&Download-Request-ID=1661629444616592

Please save copies of the unique custom URLs provided above, they will remain valid for 48 hours to download each model up to 5 times, and requests can be submitted multiple times. An email with the download instructions will also be sent to the email address you used to request the models.

Available models for download include:

  • Pretrained:

  • Llama-3.2-1B

  • Llama-3.2-3B

  • Llama-3.1-8B

  • Llama-3.1-70B

  • Llama-3.1-405B-MP16

  • Llama-3.1-405B-FP8

  • Fine-tuned:

  • Llama-3.2-1B-Instruct

  • Llama-3.2-3B-Instruct

  • Llama-3.1-8B-Instruct

  • Llama-3.1-70B-Instruct

  • Llama-3.1-405B-Instruct

  • Llama-3.1-405B-Instruct-MP16

  • Llama-3.1-405B-Instruct-FP8

  • Llama Guard:

  • Llama-Guard-3-1B

  • Llama-Guard-3-1B-INT4

  • Llama-Guard-3-8B

  • Llama-Guard-3-8B-INT8

  • Llama-Guard-2-8B

  • Llama-Guard-8B

  • Prompt-Guard-86M

Note for 405B:

  • We are releasing multiple versions of the 405B model to accommodate its large size and facilitate multiple deployment options:

  • MP16 (Model Parallel 16) is the full version of BF16 weights. These weights can only be served on multiple nodes using pipelined parallel inference. At minimum it would need 2 nodes of 8 GPUs to serve.

  • MP8 (Model Parallel 8) is also the full version of BF16 weights, but can be served on a single node with 8 GPUs by using dynamic FP8 (Floating Point 8) quantization. We are providing reference code for it. You can download these weights and experiment with different quantization techniques outside of what we are providing.

  • FP8 (Floating Point 8) is a quantized version of the weights. These weights can be served on a single node with 8 GPUs by using the static FP quantization. We have provided reference code for it as well.

  • 405B model requires significant storage and computational resources, occupying approximately 750GB of disk storage space and necessitating two nodes on MP16 for inferencing.

Code Shield

A system-level approach to safeguard tools, Code Shield adds support for inference-time filtering of insecure code produced by LLMs. This offers mitigation of insecure code suggestions risk, code interpreter abuse prevention, and secure command execution.
Now available on Github

Cybersecurity Eval

The first and most comprehensive set of open source cybersecurity safety evals for LLMs. These benchmarks are based on industry guidance and standards (e.g. CWE & MITRE ATT&CK) and built in collaboration with our security subject matter experts.
Now available on Github

Helpful tips

Please read the instructions in the

GitHub repo

and use the

provided code examples

to understand how to best interact with the models. In particular, for the fine-tuned models you must use appropriate

formatting

and correct system/instruction tokens to get the best results from the model.
You can find additional information about how to responsibly deploy Llama models in our

Responsible Use Guide

.

Review our Documentation to start building

If you need to report issues

If you or any Llama user becomes aware of any violation of our license or acceptable use policies — or any bug or issues with Llama that could lead to any such violations - please report it through one of the following means:

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