Models & capabilities

A model is an AI engine you can run. Layer exposes 500+ built-in models plus any custom styles your team has trained, all through the same endpoints.

Listing and filtering

GET /v1/workspaces/{id}/models lists the models available in a workspace. It’s paginated and supports filtering:

Filter	Purpose
`modality`	One of `image`, `video`, `three_d`, `audio`, `text`.
`search`	Free-text search over name/description.
`supports_reference_images`	Models that accept reference images.
`inpainting`, `outpainting`	Masked edit support.
`text_to_3d`, `image_to_3d`	3D generation modes.
`text_to_speech`, `sound_effect`, `generate_audio`	Audio modes.

curl "https://api.app.layer.ai/api/v1/workspaces/$WORKSPACE_ID/models?modality=image&inpainting=true" \
  -H "Authorization: Bearer $LAYER_TOKEN"

Model details

GET /v1/workspaces/{id}/models/{model_id} returns the full record, including:

capabilities — what the model supports (session modes, accepted guidance file types, duration ranges, and per-modality flags).
inference_timing — a rough runtime estimate (e.g. "5–15s").
base_model_id — the underlying base model (e.g. flux_2_pro, kling_v3_pro).
prompt_format — how prompts should be structured for this model.

Use these to decide which model fits a task and how to shape the request before you estimate and run it.

Custom trained styles

Team-trained styles appear alongside built-in models in the same list. For adapter-backed styles (LoRA), the forge weight parameter (range 0–2, default 1.0) controls style strength.

Which base models and modalities are available can vary by workspace, based on its plan and configuration.