Ollama CLI Cheatsheet - Local LLM Runtime Full Reference

Ollama is the de-facto runtime for running LLMs locally, for developers and privacy-sensitive teams who want models offline on their own machine plus one-command serving. It is far easier than hand-rolling llama.cpp, with unified model management and an OpenAI-compatible API. This sheet covers pulling/running models, tag management, Modelfile temperature/weight tuning, and serving.

AI CLI·25 commands·Last updated 2026-08-21

Run & Chat 5

ollama run llama3.1

Pull and enter interactive chat

ollama run llama3.1 "summarize in one line"

Single prompt then exit

ollama run -m

Set run parameters (e.g. context)

ollama serve

Start the local inference server (default 11434)

ollama ps

Show models currently running

Model Management 5

ollama pull <model>

Pull a model locally

ollama push <model>

Push a model to the registry

ollama list

List installed models

ollama rm <model>

Remove a local model

ollama cp <src> <dst>

Copy a model (rename/branch)

Modelfile 5

FROM llama3.1

Base model in a Modelfile

PARAMETER temperature 0.7

Set sampling temperature

SYSTEM "You are a rigorous assistant"

Set the system prompt

TEMPLATE """{{ .Prompt }}"""

Custom chat template

ollama create mymodel -f Modelfile

Build a model from a Modelfile

Serve & Port 5

ollama serve

Start the inference server in foreground

OLLAMA_HOST=0.0.0.0 ollama serve

Allow LAN access

curl http://localhost:11434/api/generate

Call the generate API

ollama show <model>

Inspect model metadata/template

ollama embeddings

Generate text embeddings

Tips 5

ollama run llama3.1 -c 4096

Cap context to save VRAM

ollama list | head

Quick peek at installed models

ollama run --verbose

Show token-speed diagnostics

ollama ps to watch VRAM

Monitor VRAM with ollama ps

ollama run <m> "translate..."

Use a local model as an offline translator

Tips

Ollama is the de-facto local runtime; a "local model" entry covers privacy/offline/zero-API-cost cases that complement cloud CLIs.
Bake behavior into a Modelfile SYSTEM/PARAMETER — more stable and versionable than repeating system instructions in prompts.
Tight on VRAM? Cap context with `-c` or watch parallel usage with `ollama ps` to avoid OOM.
For programmatic use run `ollama serve` + the REST API instead of interactive mode.

FAQ

What are the most common Ollama commands?

The daily drivers are ollama run <model> to pull and chat interactively, ollama pull <model> to download without running, ollama list to see local models, ollama ps for running models, ollama create to build a custom model from a Modelfile, and ollama serve to expose models as an OpenAI-compatible API on localhost:11434.

How do I download and run a model with Ollama?

Run something like ollama run llama3.2 — if the model is not local it is pulled from the library automatically, then you drop into a chat. To download only, use ollama pull <model>.

How do I run Ollama as an API server?

ollama serve starts a local server on port 11434 with an OpenAI-compatible /v1 API. You often do not need to start it manually because ollama run brings the backend up on demand. Point your OpenAI client base URL at http://localhost:11434 to use it.

How do I list my local Ollama models and see what is running?

ollama list shows every pulled model with size and modified time; ollama ps shows only models currently loaded in memory. Remove one with ollama rm <model>.

Official References

Each command links to its official documentation below, so you can verify the latest usage and read deeper.

Maintained by LaoHand

Publicly updated on Aug 21, 2026, continuously proofread against official docs.

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