Documentation Index
Fetch the complete documentation index at: https://docs.brightnode.cloud/llms.txt
Use this file to discover all available pages before exploring further.
The web interface for managing inference, compute, storage, API keys, usage, billing, and team resources.
Brightnode’s hosted inference entrypoint. Router gives you one OpenAI-compatible base URL for the models Brightnode makes available through the shared catalog.
A model is an inference target you can call through Router or deploy through Beams. Model IDs are passed directly in your API request, and may include slashes such as meta-llama/Llama-3.3-70B-Instruct.
A Brightnode API key is a scoped credential for programmatic access. Current key scopes are centered on Inference and Deployments.
A dedicated GPU or CPU instance for containerized AI/ML workloads, such as training models, running inference, or other compute-intensive tasks.
Persistent storage that exists independently of your other compute resources. Network volumes are designed for durable datasets, checkpoints, and shared assets across Brightnode workflows.
The preview deployment workflow for managed inference models. Beams is intended for cases where you need deployment-level control instead of the shared hosted inference router.
The console views for request count, token usage, latency, and cost across your inference traffic.
Container
A Docker-based environment that packages your code, dependencies, and runtime into a portable unit that runs consistently across machines.
Data center
Physical facilities where Brightnode’s GPU and CPU hardware is located. Your choice of data center can affect latency, available GPU types, and pricing.
Machine
The physical server hardware within a data center that hosts your workloads. Each machine contains CPUs, GPUs, memory, and storage.
