> ## Documentation Index
> Fetch the complete documentation index at: https://notes.kodekloud.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Essential Ollama CLI Commands
> Streamline your local AI model workflow with the Ollama CLI, mirroring Docker syntax for easy command usage.
Streamline your local AI model workflow with the Ollama CLI. If you have experience with [Docker](https://www.docker.com), many of these commands will feel instantly familiar.
Most Ollama commands mirror Docker syntax for running, listing, and managing images—making it easy to get started if you’ve used Docker before.
## Quick Reference
| Command | Purpose | Example |
| ----------- | ------------------------------------------- | ------------------------ |
| ollama run | Pull (if needed) and start a model | `ollama run MODEL_NAME` |
| ollama stop | Terminate a background model | `ollama stop MODEL_NAME` |
| ollama list | Display all local models | `ollama list` |
| ollama rm | Remove a model to free disk space | `ollama rm MODEL_NAME` |
| ollama pull | Download a model without launching it | `ollama pull MODEL_NAME` |
| ollama show | Inspect model metadata (quantization, etc.) | `ollama show MODEL_NAME` |
| ollama ps | List currently running models | `ollama ps` |
***
## ollama run
Start a model session. If the specified model isn’t on your machine, Ollama will:
1. Download its manifest and layers
2. Verify the SHA-256 digests
3. Save the manifest locally
4. Launch an interactive chat interface
```bash theme={null}
$ ollama run MODEL_NAME
pulling manifest
pulling 633fc5be925f... 100%
pulling fa8235e5b48f... 100%
pulling 542b217f179c... 100%
pulling 8de1baf1db0... 100%
pulling 23291dc44752... 100%
verifying sha256 digest
writing manifest
success
```
***
## ollama stop
When you run a model in the background (e.g., via `&` on Unix), stop it gracefully with:
```bash theme={null}
$ ollama stop MODEL_NAME
```
This frees up GPU/CPU resources immediately.
***
## ollama list
List all models stored on your local host, along with their IDs, sizes, and last modification times. Use this to identify large or outdated models:
```bash theme={null}
$ ollama list
NAME ID SIZE MODIFIED
phi3:latest 4f2229297938 2.2 GB 20 hours ago
qwen:latest d53d04290064 2.3 GB 12 days ago
mistral:latest f974a74358d6 4.1 GB 13 days ago
llama3.2:latest a80c4f17acd5 2.0 GB 13 days ago
```
***
## ollama rm
Remove a model from your system to reclaim disk space. You can always re-pull it later.
```bash theme={null}
$ ollama rm MODEL_NAME
deleted 'MODEL_NAME'
```
***
## ollama pull
If you want to prefetch a model without starting it immediately, use:
```bash theme={null}
$ ollama pull MODEL_NAME
pulling manifest
pulling dde5aa3fc5ff... 100% 2.0 GB
pulling 966de95ca8a6... 100% 1.4 KB
pulling fcc5a6bec9da... 100% 7.7 KB
pulling a70ff7e570d9... 100% 6.0 KB
pulling 56bb8bd477a5... 100% 96 B
pulling 34bb5ab01051... 100% 561 B
verifying sha256 digest
writing manifest
success
```
After pulling, a subsequent `ollama run MODEL_NAME` will skip downloads.
***
## ollama show
Inspect model metadata—such as license details and quantization format—without running it:
```bash theme={null}
$ ollama show llama3.2
License
LLAMA 3.2 COMMUNITY LICENSE AGREEMENT
Llama 3.2 Version Release Date: September 25, 2024
quantization Q4_K_M
...
```
You can also view model details on the [Ollama website](https://ollama.com) or from within a running session via the `/show` command.
***
## ollama ps
Similar to `docker ps`, this command lists all active model processes, their resource consumption, and remaining runtime:
```bash theme={null}
$ ollama ps
NAME ID SIZE PROCESSOR UNTIL
phi3:latest 4f2229297938 6.6 GB 100% GPU 4 minutes from now
llama3.2:latest a80c4f17acd5 4.0 GB 100% GPU 4 minutes from now
```
Keep an eye on running models. Stopping unused ones prevents unnecessary GPU/CPU usage and conserves system memory.
***
These core commands will help you manage Ollama models effectively. Happy modeling!