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docs(platforms): macOS trains on CPU by design (no Apple-GPU path from containers) #126

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2 changes: 1 addition & 1 deletion environment-setup/configuration.mdx
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Expand Up @@ -85,7 +85,7 @@ Auto-detected. ROCm is installed automatically on Ubuntu and RHEL/CentOS. A logo

### macOS

CPU only. Docker Desktop on macOS does not support GPU passthrough. For GPU workloads, deploy on a Linux machine with NVIDIA GPUs or use [AWS (EKS)](/environment-setup/eks-client-deployment-guide).
CPU only, on both Intel and Apple silicon. Training runs inside Linux containers, which on macOS run in a virtual machine with no access to the Apple GPU — so macOS machines train on CPU by design, regardless of device settings. For GPU training, use a machine with an NVIDIA GPU (Linux, or Windows via WSL2), or deploy on [AWS (EKS)](/environment-setup/eks-client-deployment-guide).

### Windows

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2 changes: 1 addition & 1 deletion environment-setup/deployment-environments.mdx
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Expand Up @@ -9,7 +9,7 @@ tracebloc runs the same way everywhere: one chart (`tracebloc/client`), one set

| Environment | Runs on | GPU | Best when |
|---|---|---|---|
| [Local / k3d](/environment-setup/deploy-local) | One machine you own | NVIDIA / AMD, auto-detected | A laptop or a single on-prem server — the fastest start |
| [Local / k3d](/environment-setup/deploy-local) | One machine you own | NVIDIA / AMD, auto-detected (macOS: CPU only) | A laptop or a single on-prem server — the fastest start |
| [Bare-metal](/environment-setup/deploy-bare-metal) | Your own Kubernetes cluster | Your nodes | You already run on-prem Kubernetes |
| [Amazon EKS](/environment-setup/eks-client-deployment-guide) | AWS (managed) | GPU nodegroups | You're on AWS and want managed, autoscaling compute |
| [Azure AKS](/environment-setup/deploy-aks) | Azure (managed) | GPU node pools | You're on Azure |
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