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A Model is a specific LLM your agents can pick — main engine, secondary engine, or as the tenant’s text / multimodal default. Each model belongs to a Provider. Models are managed in Command Center → Settings → Models.
Models catalog

Settings → Models: every model an agent can select sits in this catalog, with context length, status, and pricing.

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Fields

Advanced sampling parameters (temperature, top P, top K, presence/frequency penalty, max output tokens, seed, stop sequences) can be set per model. You can also record pricing plans per model and run an on-demand performance test that reports reachability, time to first token, and throughput.

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Thinking effort

A thinking-effort level trades depth of reasoning against latency and cost:
Some custom or compatible providers do not accept a reasoning argument and reject any request that includes one. If your provider does not support reasoning, leave thinking effort unset — do not select any level.

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Tenant defaults

The tenant’s default Text LLM model and Multimodal model are chosen in Settings → Tenant from the catalog’s enabled models. Only image-capable models appear as Multimodal options. These defaults power gateway routing, the AI Assistant, knowledge ingestion, and any agent that doesn’t pick its own engines. See Engine & Agents for how agents combine main and secondary models, and where the tenant defaults are used.

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Deletion rule

A model assigned to any agent — main or secondary — cannot be deleted. Reassign those agents or disable the model instead.

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Deploy-time seeding

On deploy, the installer seeds models from the providers detected in the engine environment. After that, management moves to Command Center — no engine restart needed.