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The Endpoints screen lists your running models: “Running models you can call. Each one bills only while it is running.” From here you deploy base models, open an endpoint to manage it, and reach Aliases.
Valkyrie Endpoints screen

Endpoints: every deployment, with its URL, type, and status.

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The endpoints list

Tabs filter by Active, All, Failed, and Terminated, each with a count. Search by name to find an endpoint across every page, and click a column header to sort your whole list. Each row shows: The buttons at the top right open Aliases and Deploy a base model.

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Deployment stages

An endpoint is only ready to use once it reaches Running. While it starts, it passes through:
Preparing means the machine is up and the runtime and model files are being set up. The screen shows this progression live, so you can see exactly where a starting endpoint is.
Large models can take a while to start. If an endpoint is still starting after 25 minutes, the dashboard shows Taking longer than usual. If the machine never becomes reachable, Valkyrie stops it automatically about 20 minutes after it comes up, with an error that explains why, so you are not billed for a machine you cannot use.

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Endpoint detail

Click an endpoint to open it. The page has three tabs: Overview, Webhooks, and Access.
Valkyrie endpoint detail screen

An endpoint's Overview tab, with its URL ready to copy.

Overview shows the status pill and a Base model or Fine-tuned pill, when the endpoint was created, and the GPU it runs on. The Endpoint section has:
  • The Endpoint URL with a Copy button.
  • The alias pointing at it, or a Create one link if there is none.
  • The URL slug, which you can change with Rename URL.
The actions for the endpoint are in its menu.

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Operate an endpoint

A running endpoint holds a GPU and costs money even when idle. Use stop/resume or a schedule to control spend, see Wallet & billing.

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Share an endpoint

On the Access tab you can grant teammates access by email. The owner can see who has access and which keys each person holds, and can revoke access, which invalidates the keys tied to that grant. Endpoints shared with you are marked in the list and when you create a key.

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Deploy a base model

A base model is served as it is, with no fine-tune. Open Deploy a base model from Endpoints, from Home (“No fine-tune needed? Deploy a base model as it is”), or from the Models list.
Valkyrie Deploy a base model screen

Deploy a base model: pick a preset or enter any Hugging Face model path.

1

Choose the model

Search the presets by name or Hugging Face path. Each preset shows the GPU type it needs, its memory, and tags such as tool calling. Or enter any Custom HuggingFace model path.
2

Configure and deploy

Review the configuration, add an optional alias, and deploy. You land on the new endpoint’s page, where you can follow its stages to Running.

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Deploy a fine-tuned version

When a version on Models has completed, click Deploy to open its deploy page.
1

Pick the serving settings

Under Serving settings, choose the Hardware from a GPU list that shows the price per hour and the memory per card. Choose the Engine: vLLM (recommended) or Ollama. The Advanced section lets you set the context length, memory use, and an optional cluster name. Traffic-based run tiers (“How much traffic?”) are marked Coming soon.
2

Check the summary

The Summary shows the model, hardware, engine, and Cost while running per hour. Billed from your wallet while the endpoint runs. Stop it any time from its page.
3

Deploy

Click Deploy endpoint. You land on the new endpoint’s page.
Once a version is deployed, its page on Models links to the running endpoint instead of showing Deploy.

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Call the endpoint

A ready endpoint exposes an OpenAI-compatible API at its URL (/{deployment_slug}/v1/...). Attach an alias for a memorable URL, try it first in the Playground, and see Run inference for request examples.
A fine-tuned endpoint serves its model as fine-tuned-<job id>. You do not need to match that name exactly: Valkyrie routes requests sent to the endpoint’s URL to your fine-tuned model whatever model name the client sends.