Models, deployments, and jobs
Fine-tuning job
A training run that adapts an open base model to your dataset using a managed
Unsloth pipeline. Produces model outputs (weights/adapters) stored for you.
Deployment
A running, servable model behind an OpenAI-compatible endpoint. It can serve a
fine-tuned model or any Hugging Face base model, using vLLM or Ollama.
GPUs are provisioned on demand
Valkyrie doesn’t keep idle GPUs around. When you launch a job or a deployment, it provisions a GPU from a cloud marketplace, runs your workload, and releases it when it’s no longer needed. Deployments can auto-stop when idle and be resumed on demand, so you pay for compute you actually use.You never manage GPU machines, drivers, or serving infrastructure yourself.
Valkyrie handles provisioning, setup, health monitoring, and teardown.
The wallet
Billing is prepaid and per-use. You add credit to a wallet, and jobs and deployments draw against it. Your balance is computed from the full ledger of credits and debits, so every charge and top-up is auditable. See Quota & billing.Aliases
An alias is a stable, human-readable name for a deployment. Instead of calling a raw deployment slug, you call:Ways to use Valkyrie
Dashboard
The web app for people: manage keys, datasets, jobs, deployments, and spend.
OpenAI-compatible API
Call your deployed models from any OpenAI-compatible client or SDK.
MCP server
Let an AI agent provision, deploy, and operate models programmatically.
Authentication at a glance
API keys are prefixed by purpose, for example, deployment keys begin with
vk_dep_ and MCP keys begin with vk_mcp_. See
Authentication.