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This takes you from an empty machine to a rendered scenario. Step 3 runs on SimForge cloud and needs no GPU, no runtime and no download: no GPU? start there. Step 4 adds the local runtime and a map to author and render on your own machine; check what the machine needs first.

1. Install the CLI

2. Sign in

simforge login alone opens a browser on this machine instead. Sign in covers API keys for machines nobody can approve a code for.

3. No GPU? Start here: author and render on SimForge cloud

The scenario is a hosted draft with a local copy; authoring discover lists the map’s real lanes (rsl, lengthM) to place actors on. 2D renders are free, and every cloud run still takes an explicit --max-cost in cents: run it with --stage instead first to save it and see the price. A 3D render is the same command with --mode 3d --rig rig.json and a cost cap (Preview and render).

4. Locally: the runtime and a map

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, and refuses one that cannot fit on the disk before it starts. For authoring and 2D renders only, leave out --for 3d: the 2D runtime and the 2D map are megabytes instead of gigabytes.
Then add actors with typed authoring operations. 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.
The 3D render needs an NVIDIA GPU with at least 8 GiB or Apple M3 or newer, and uses one front camera on the ego: 1280x720 at 24 fps, the showcase preset, locally and with --cloud. In Docker, start the container with the NVIDIA runtime’s graphics capability (Running in Docker); plain --gpus all cannot start Vulkan. Preview and render covers other rigs, presets, texture tiers and the output format.