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Exploring the Location of Ollama Models on Local Machine

Exploring the Location of Ollama Models on Local MachinePermalink

ObjectivePermalink

Many times you may have a question like, I have installed ollama in wsl and download some ollama models. Ollama list shows me those models. I want to know where they are stored. Why it is needed? Because you want to use that location as volume in your docker container. And you don’t want to download the model everytime you start the container neither you want to have duplicate copy of the same model on your machine or network.

If you want to try these commands and see the results then following is the requisites.

  • Windows 11
  • WSL 2
  • Ubuntu or other variation of linux
  • Docker Desktop for Windows in Ubuntu (WSL)
  • Ollama on Ubuntu (WSL)
  • You have downloaded some model from ollama.com

How to check the location of ollama models?Permalink

$ ollama list 

NAME                  ID              SIZE      MODIFIED
openthinker:latest    aaffe05a5e2e    4.7 GB    3 hours ago
qwen2.5-coder:7b      2b0496514337    4.7 GB    24 hours ago

Docker VolumesPermalink

Check if they’re in the Docker volumes since Ollama uses containers:

$ docker volume ls
    DRIVER    VOLUME NAME
    local     ollama
    local     open-webui

$ docker volume inspect ollama

[
    {
        "CreatedAt": "2025-02-20T08:47:30Z",
        "Driver": "local",
        "Labels": null,
        "Mountpoint": "/var/lib/docker/volumes/ollama/_data",
        "Name": "ollama",
        "Options": null,
        "Scope": "local"
    }
]

Look at where Ollama is running fromPermalink

$ which ollama
/usr/local/bin/ollama

$ ps aux | grep ollama
ollama     153  0.0  1.1 35986124 179864 ?     Ssl  09:46   0:02 /usr/local/bin/ollama serve
hari       547  0.0  0.2 1999704 33152 pts/0   Sl+  10:11   0:00 ollama run openthinker:latest
hari      1283  0.0  0.0   4092  2000 pts/3    S+   11:37   0:00 grep --color=auto ollama

Track location while downloadPermalink

If you’re downloading a new model, you can monitor in real-time where it’s being saved:

$ journalctl -fu ollama

Feb 20 10:18:06 Hari-MSI ollama[153]: time=2025-02-20T10:18:06.048Z level=WARN source=sched.go:646 msg="gpu VRAM usage didn't recover within timeout" seconds=5.123075429 model=/usr/share/ollama/.ollama/models/blobs/sha256-b00569cd7782c6d7f1eb1d0a005b3a112fc879ee746111e3afea4b405d7776c1
Feb 20 10:18:06 Hari-MSI ollama[153]: time=2025-02-20T10:18:06.298Z level=WARN source=sched.go:646 msg="gpu VRAM usage didn't recover within timeout" seconds=5.372942367 model=/usr/share/ollama/.ollama/models/blobs/sha256-b00569cd7782c6d7f1eb1d0a005b3a112fc879ee746111e3afea4b405d7776c1
Feb 20 10:18:06 Hari-MSI ollama[153]: time=2025-02-20T10:18:06.548Z level=WARN source=sched.go:646 msg="gpu VRAM usage didn't recover within timeout" seconds=5.622979384 model=/usr/share/ollama/.ollama/models/blobs/sha256-b00569cd7782c6d7f1eb1d0a005b3a112fc879ee746111e3afea4b405d7776c1
Feb 20 10:52:51 Hari-MSI ollama[153]: [GIN] 2025/02/20 - 10:52:51 | 200 |     170.514µs |       127.0.0.1 | HEAD     "/"
Feb 20 10:52:51 Hari-MSI ollama[153]: [GIN] 2025/02/20 - 10:52:51 | 200 |    2.147892ms |       127.0.0.1 | GET      "/api/tags"
Feb 20 11:35:59 Hari-MSI ollama[153]: [GIN] 2025/02/20 - 11:35:59 | 200 |      46.505µs |       127.0.0.1 | HEAD     "/"
Feb 20 11:35:59 Hari-MSI ollama[153]: [GIN] 2025/02/20 - 11:35:59 | 200 |     332.731µs |       127.0.0.1 | GET      "/api/tags"
Feb 20 11:41:00 Hari-MSI ollama[153]: [GIN] 2025/02/20 - 11:41:00 | 200 |      27.668µs |       127.0.0.1 | HEAD     "/"
Feb 20 11:41:00 Hari-MSI ollama[153]: [GIN] 2025/02/20 - 11:41:00 | 404 |      378.22µs |       127.0.0.1 | POST     "/api/show"
Feb 20 11:41:02 Hari-MSI ollama[153]: time=2025-02-20T11:41:02.459Z level=INFO source=download.go:176 msg="downloading 96c415656d37 in 16 292 MB part(s)"

Model after download are kept in /usr/share/ollama/.ollama

What are the other location for keeping model?Permalink

It’s quite interesting how different LLM providers structure their model storage! Let us see the common default locations for popular LLM frameworks:

  1. Ollama: ``` By default, Ollama stores its models in the following locations:
  • On macOS: ~/.ollama/models
  • On Linux: ~/.ollama/models
  • On Windows: C:\Users\<username>\.ollama\models
  • On Linux: ‘/usr/share/ollama/.ollama/models/`

Keep in mind in Linux ~ means home directory, in my case /home/hari.


2. Hugging Face:

~/.cache/huggingface/hub/


3. LangChain:

~/.cache/langchain/


4. Local LLaMA models (when using llama.cpp):

./models/ (in the llama.cpp directory)


5. Text-generation-webui:

./models/ (in the text-generation-webui directory)


6. GPT4All:

~/.nomic/ (on Linux/WSL) C:\Users[USERNAME]\AppData\Local\nomic.ai\GPT4All\ (on Windows)


7. LocalAI:

./models/ (in the LocalAI directory)


The storage patterns usually fall into three categories:
- Hidden directories in home folder (`.cache`, `.local`, etc.)
- System-wide locations (`/usr/share/`, `/var/lib/`)
- Application directory (`./models/`)

## How to customize these locations?

To customize the storage location for Ollama models, you can use the `OLLAMA_MODELS` environment variable before starting the Ollama service:

```bash
# Linux/macOS
export OLLAMA_MODELS=/path/to/custom/ollama/models
ollama serve

# Windows PowerShell
$env:OLLAMA_MODELS="D:\path\to\custom\ollama\models"
ollama serve

If you’re running Ollama in a Docker container, you can customize the storage location by mounting a volume:

docker run -d -v /host/path/to/models:/root/.ollama/models -p 11434:11434 ollama/ollama

here
/host/path/to/models (frist before :) => Folder location from the hosting machine 
/root/.ollama/models (second after :) => folder location on docker.
11434 (before :) => 11434 is the container's internal port (where Ollama runs inside Docker)
11434 (after :) => 11434 is port exposed on your host machine

Note that if you change the model storage location after downloading models to the default location, you’ll need to either:

  1. Move your existing models to the new location, or
  2. Re-download the models to the new location

Run Open-WebUi on localhost using downloaded modelsPermalink

Let’s you have a conainer and you want to use a already downloaded model within this container. In this example I have taken a docker image of open-webui. It is very popular Web interface (chatgpt kind of UI) for open source models or integrating other API based models.

You need to run this command within Ubuntu (wsl2).

docker run -d \
  -p 3000:8080 \
  --gpus=all \
  -e WEBUI_AUTH=False \
  -v /usr/share/ollama/.ollama:/root/.ollama \
  -v open-webui:/app/backend/data \
  --name open-webui \
  --restart always \
  ghcr.io/open-webui/open-webui:ollama

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About the Author

Author avatar

Dr. Hari Thapliyal is a prolific blogger and seasoned professional with an extensive background in Data Science, Project Management, and Advait-Vedanta Philosophy. He holds a Doctorate in AI/NLP from SSBM, Geneva, along with Master’s degrees in Computers, Business Management, Data Science, and Economics. With over three decades of experience in management and leadership, Hari has extensive expertise in training, consulting, and coaching within the technology sector. His specializations include Data Science, AI, Computer Vision, NLP, and machine learning. Hari is also passionate about meditation and nature, often retreating to secluded places for reflection and peace.

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