Create a template
Authorizations
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Body
Reusable container configuration shared across templates, pods, and serverless endpoints. Adding a field here automatically propagates to all three resources.
Docker image reference
"runpod/pytorch:2.8.0-py3.11-cuda12.8.1"
1"My PyTorch Template"
Hardware family this template targets.
CPU— CPU-only workloadsNVIDIA— NVIDIA GPU workloadsAMD— AMD GPU workloads
CPU, NVIDIA, AMD Arguments passed to the container entrypoint
""
Container disk in GB (ephemeral, wiped on restart)
x >= 150
Exposed ports, formatted as port/protocol
["8888/http", "22/tcp"]Environment variables as key-value pairs
{ "JUPYTER_PASSWORD": "hunter2" }Container registry credential ID (for private images)
null
Storage mounts attached to a template. Templates support only a
single persistent mount today; any network property is rejected
with 422 by the schema validator.
PATCH semantics: omitting mounts or sending {} leaves the
existing mount unchanged.
Response
Created
Reusable container configuration shared across templates, pods, and serverless endpoints. Adding a field here automatically propagates to all three resources.
Docker image reference
"runpod/pytorch:2.8.0-py3.11-cuda12.8.1"
Arguments passed to the container entrypoint
""
Container disk in GB (ephemeral, wiped on restart)
x >= 150
Exposed ports, formatted as port/protocol
["8888/http", "22/tcp"]Environment variables as key-value pairs
{ "JUPYTER_PASSWORD": "hunter2" }Container registry credential ID (for private images)
null
"tpl_abc"
"My PyTorch Template"
Storage mounts attached to a template. Templates support only a
single persistent mount today; any network property is rejected
with 422 by the schema validator.
PATCH semantics: omitting mounts or sending {} leaves the
existing mount unchanged.
Whether this template is for serverless workers (true) or pods (false)
false
Whether this template is visible to other RunPod users
false
Hardware family this template targets.
CPU— CPU-only workloadsNVIDIA— NVIDIA GPU workloadsAMD— AMD GPU workloads
CPU, NVIDIA, AMD