# Quickstart

> From nothing to rendered frames on your own Linux machine - install the CLI, sign in, install the runtime and a map, and render a scenario in 3D and 2D.

Source: https://simforge.ai/docs/quickstart

This takes you from an empty machine to camera frames, instance-id, depth and semantic passes, and a video, rendered locally. Check [what the machine needs](/docs/install#what-the-machine-needs) first: Linux x86_64 (Ubuntu 24.04 or later), an Apple silicon Mac or Windows x64; for 3D an NVIDIA GPU with at least 8 GiB, or Apple M3 or newer. In Docker, start the container with the NVIDIA runtime's graphics capability ([Running in Docker](/docs/install#running-in-docker)); plain `--gpus all` cannot start Vulkan.

## 1. Install the CLI

```sh
curl -fsSL https://simforge.ai/install.sh | sh
```

## 2. Sign in, accept the agreement, install the runtime

```sh
simforge login --device                    # prints a URL and a code; approve it in your browser
simforge runtime license                   # read the agreement; nothing is accepted yet
simforge runtime install --accept-license  # accepts that exact version, then downloads the runtime
simforge doctor                            # what is installed, and the fix for anything missing
```

Accepting the agreement is what entitles your account to the runtime and the maps. Every download is signed by SimForge: the CLI checks the signature and the sha256 of each archive before it installs anything.

## 3. A scenario and its map

```sh
simforge maps pull easterbrook-discovery-school --accept-license
simforge scenario new --map easterbrook-discovery-school --out s.json
```

Then add actors with [typed authoring operations](/docs/scenarios). A scenario from the SIMLOG-25k dataset works the same way: download its whole folder and pull the map it names.

The SIMLOG-25k dataset is on Hugging Face: `huggingface.co/datasets/SIMFORGE-AI/simlog-25k`.

## 4. Render

```sh
simforge render s.json --mode 3d --out frames        # photoreal, one front camera
simforge render s.json --mode 2d --out topdown       # top-down video, no GPU needed
```

The 3D render uses one front camera on the ego: 1280x720 at 24 fps, the `showcase` preset, locally and with `--cloud`. [Preview and render](/docs/render) covers other rigs, presets, texture tiers and the [output format](/docs/render#output-format); add `--cloud --max-cost <cents>` to render the same scenario on SimForge's GPUs instead.