Indie developers: separate builds from daily coding
Start with GNU Core M4 and choose a location and rental term that work for you. Once you receive your credentials, check project dependencies via screen sharing, then run an Xcode Archive over SSH or with a build script.
Set up signing assets with the right team permissions and verify your Xcode and SDK versions. When the build is done, export the app package, symbol files, and build logs. Run overnight jobs on the cloud Mac while your local machine stays free for interactive development.
CI teams: add a dedicated runner for a busy release cycle
Choose a configuration for your project’s workload, validate the environment with a full pipeline run, then register the Mac as a self-hosted runner. Split code checkout, dependency installation, testing, signing, and archiving into stages you can troubleshoot independently.
For multiple machines, name them by location, project, and purpose so a test machine isn’t mistaken for a release machine. Before your rental ends, unregister the runner, revoke access tokens, and document your build-cache and artifact retention policies.
AI experiments: test the workload before committing long term
For memory-intensive work, choose GNU Studio M4: M4 / 24GB / 512GB. Set up the environment for MLX or llama.cpp, and first check model file size, quantization, and runtime memory use.
Record results using the same prompts, context length, and parameters; don’t compare runtimes from different conditions. For larger models and datasets, choose an optional +1TB SSD or +2TB SSD, and export your results before the rental ends.
Media workflows: keep batch jobs remote
Estimate the total space needed for source media, proxies, caches, and exports before deciding whether the base disk is enough. Upload media over SFTP, confirm the required software and licensing, then set up transcoding or batch exports.
Use screen sharing to check visuals and job status, and file transfer to hand off deliverables. Verify encoding settings with a short clip before processing the full batch. When the job is done, transfer the finished media and project files back; don’t rely on the remote disk as your only archive.