Features and limitations

What you can do

• Run local models with Ollama or vLLM on eligible CPU/GPU targets.
• Use FreeToken's dedicated configuration on its supported NVIDIA hardware.
• Experiment with Realtime through the separate vLLM-Omni profile.
• Connect external model providers and use a common LiteLLM API.
• Create applications from the service catalog and grant access to specific users or groups.
• Share running local chat models through the opt-in Private Mesh module.
• Manage local users, GPU allocation, host networking, model cache and Ubuntu updates.
• Use the browser dashboard or authenticated CLI/TUI; advanced users can manage runtime resources.

What is not automatic

A detected GPU is not proof that every engine or model will run. The dashboard checks engine capabilities, driver readiness, allocation slots and memory data. See the compatibility matrix.

GPU sharing permits more workloads to use a device; it does not multiply its physical memory or provide isolated VRAM limits. Memory estimates do not prove that a particular context length will fit. Downloading large checkpoints may also need substantial disk space beyond their final size.

FreeToken and vLLM-Omni have their own runtime boundaries. An OpenAI-compatible chat endpoint does not automatically provide /v1/realtime or audio output.

There is no appliance-wide one-click backup/restore or supported factory-reset button. Backup and recovery requires a planned, separately tested procedure. A Flux update does not upgrade the Ubuntu release.

Access and licensing

Local identity, model runtimes, GPU management, Resource Sharing and Private Mesh do not require a license file. Federated SSO requires Free Registered or Commercial activation. Technical activation and legal permission for production use are different questions; LICENSING.md and LICENSE are the authoritative terms.

See license management for the dashboard workflow.