[role="xpack"]
[[delete-trained-models]]
= Delete trained models API
[subs="attributes"]
++++
<titleabbrev>Delete trained models</titleabbrev>
++++

Deletes an existing trained {infer} model.


[[ml-delete-trained-models-request]]
== {api-request-title}

`DELETE _ml/trained_models/<model_id>`


[[ml-delete-trained-models-prereq]]
== {api-prereq-title}

Requires the `manage_ml` cluster privilege. This privilege is included in the 
`machine_learning_admin` built-in role.


[[ml-delete-trained-models-path-params]]
== {api-path-parms-title}

`<model_id>`::
(Optional, string)
include::{es-ref-dir}/ml/ml-shared.asciidoc[tag=model-id]

[[ml-delete-trained-models-query-parms]]
== {api-query-parms-title}

`force`::
  (Optional, Boolean) Use to forcefully delete a trained model that is referenced
  by ingest pipelines or has a started deployment.

[[ml-delete-trained-models-response-codes]]
== {api-response-codes-title}

`409`::
  The code indicates that the trained model is referenced by an ingest pipeline
  and cannot be deleted.


[[ml-delete-trained-models-example]]
== {api-examples-title}

The following example deletes the `regression-job-one-1574775307356` trained
model:

[source,console]
--------------------------------------------------
DELETE _ml/trained_models/regression-job-one-1574775307356
--------------------------------------------------
// TEST[skip:TBD]

The API returns the following result:


[source,console-result]
----
{
  "acknowledged" : true
}
----