Model Governance (Settings → Models)

Stage: Settings (admin) · What it does: control which models can be used for which functionality across the platform — like the Instances tab does for GPU types. Admins set tenant-wide defaults and per-user overrides; every model-backed feature (Ask AI, judges, LLM Format, custom assistants, chat) checks this gate on every call.


Why it matters


The purposes (what "functionality" means)

Each model can be granted one or more purposes. These map directly to platform features:

Purpose Feature it gates
Ask AI The Ask AI assistant in the console
Chat General chat surfaces
Assistant Custom AI assistants you build and embed
LLM Format The LLM Format pipeline node (formatting training data)
Judge LLM-as-judge (quality review of generated rows, gateway safety checks)
Glossary Glossary AI
Notebook Notebook agent
Guide Guided-workspace help agent
Healer Self-healing assistant
Embed Embeddings (Titan)

A model's capabilities are fixed in the catalog — you can only grant purposes a model actually supports (you can't make an embeddings model do chat).


How it works (resolution order)

When any feature uses a model, the platform resolves the effective grant for that user, highest wins:

Per-user override  →  role (their role's Models)  →  tenant default  →  catalog default

Your per-user "allowed models" are what the model dropdowns actually show you — if a model isn't granted, it doesn't appear as an option.

Deployed endpoints are exempt by design. A model you deployed yourself (deploy:…), a BYO endpoint, or a legacy DeepSeek id is your model serving whatever you pointed it at — the gate only governs the platform's managed catalog models.


How to use (admin)

  1. Settings → Models.
  2. Tenant defaults: set the model × purpose grid for the whole tenant, then Save. - Unchecking a cell = that model is not available for that purpose in this tenant. - Saving an empty grid clears the override — back to catalog defaults (never "deny everything").
  3. Per-user overrides: pick a user, set their grid, Save. Clear removes their override.
  4. Model rows show price per 1M tokens and region availability — the numbers an admin needs to decide "should this be on?".

Real-world examples

🏦 Financial services — model approval workflow

A bank's ML platform team approves exactly three models for production: the default DeepSeek v3.2 for Ask AI + judges, Llama 3.3 70B for LLM Format, and Nova Micro for assistants. The tenant default grid encodes that; a data scientist who tries to use Claude for LLM Format finds it simply isn't in the dropdown. Their vendor review is "here's the grid" — one screen.

🧑‍💼 SaaS — pilot user, then rollout

A SaaS company enables a new Qwen model for a pilot user first (per-user override), watches cost and quality for a week, then promotes it to the tenant default.

🏥 Healthcare — least privilege per role

A health system gives researchers the small local models only (Gemma/Llama 8B), keeps frontier models admin-only, and locks the embeddings model to the pipeline role — PHI-bearing features run on the smallest capable model by policy.


Gotchas