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Luna Studio is only available in the Enterprise tier of Galileo and is deployed by Galileo into your own cluster or cloud. Contact us to learn more and get started.
Luna Studio is the self-service fine-tuning web app for Luna-2 custom evaluation metrics. Because Luna-2 itself is an enterprise-tier capability, Luna Studio inherits the same availability model — it ships as part of an enterprise Galileo deployment, not as a shared SaaS product.

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Who can use Luna Studio

Luna Studio is available to enterprise customers of Galileo.
  • There is no public sign-up at a shared app.luna-studio.ai-style URL.
  • Each customer org reaches their Luna Studio at the URL Galileo provisions for them (typically alongside their Galileo console).
  • Once provisioned, anyone in the customer’s org can sign in, create projects, and launch training runs — see the Quickstart.
If your team is on the standard tier of Galileo today and you want access to Luna Studio, contact us.

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How Luna Studio is deployed

Galileo provisions Luna Studio into the customer’s own infrastructure. The training jobs that fine-tune Luna base models run on a training platform chosen at deployment time:
  • Kubernetes
  • Vertex AI Pipelines
  • AzureML Pipelines
  • SageMaker Pipelines
The GPU fine-tuning jobs run inside your environment against the capacity and quotas your team manages. Synthetic data generation is orchestrated by Luna Studio but calls the supported runtime LLM provider and model you select.

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What’s fixed at deployment vs. configurable in-app

Luna Studio splits its integrations into two layers. Understanding which layer a setting lives on tells you whether you change it in the UI or talk to your Galileo contact. The deployment-level layer is what these docs mean when they reference “your Luna Studio deployment” — for example, the base model list shown in Step 4 of the new run flow is sourced from your deployment. The runtime layer includes the supported LLM keys and Galileo records users configure in the app, plus projects and runs. The Galileo exception is current implementation behavior, not a permanent architectural classification: although personal and workspace-scoped galileo_api records can be saved in the UI, dataset import and metric registration currently ignore both and read deployment settings instead. See Galileo integration for the operational setup and verification path. For more on the runtime layer, see Integrations overview. For more on the training platform list, see Training platforms.

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How to get Luna Studio

Contact sales

Talk to Galileo about enabling Luna Studio for your org.

Quickstart

Already provisioned? Walk through your first end-to-end training run.