Create a template

Creates a reusable container-configuration preset — image, disk, ports, env, registry, and mount settings — for pods and serverless endpoints. createPod and createEndpoint don’t take a template ID; instead, spread a template’s fields into the request body directly. Returns the created template.

POST /v2/templates

Create a template

cURL

curl --request POST \
  --url https://api.runpod.io/v2/templates \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "PyTorch GPU Template",
  "image": "runpod/pytorch:2.8.0-py3.11-cuda12.8.1",
  "category": "NVIDIA",
  "disk": 50,
  "ports": [
    "8888/http"
  ],
  "env": {
    "JUPYTER_ENABLE_LAB": "yes"
  },
  "mounts": {
    "persistent": {
      "size": 20,
      "path": "/workspace"
    }
  },
  "serverless": false,
  "public": false
}
'

import requests

url = "https://api.runpod.io/v2/templates"

payload = {
    "name": "PyTorch GPU Template",
    "image": "runpod/pytorch:2.8.0-py3.11-cuda12.8.1",
    "category": "NVIDIA",
    "disk": 50,
    "ports": ["8888/http"],
    "env": { "JUPYTER_ENABLE_LAB": "yes" },
    "mounts": { "persistent": {
            "size": 20,
            "path": "/workspace"
        } },
    "serverless": False,
    "public": False
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: 'PyTorch GPU Template',
    image: 'runpod/pytorch:2.8.0-py3.11-cuda12.8.1',
    category: 'NVIDIA',
    disk: 50,
    ports: ['8888/http'],
    env: {JUPYTER_ENABLE_LAB: 'yes'},
    mounts: {persistent: {size: 20, path: '/workspace'}},
    serverless: false,
    public: false
  })
};

fetch('https://api.runpod.io/v2/templates', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.runpod.io/v2/templates",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'name' => 'PyTorch GPU Template',
    'image' => 'runpod/pytorch:2.8.0-py3.11-cuda12.8.1',
    'category' => 'NVIDIA',
    'disk' => 50,
    'ports' => [
        '8888/http'
    ],
    'env' => [
        'JUPYTER_ENABLE_LAB' => 'yes'
    ],
    'mounts' => [
        'persistent' => [
                'size' => 20,
                'path' => '/workspace'
        ]
    ],
    'serverless' => false,
    'public' => false
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.runpod.io/v2/templates"

	payload := strings.NewReader("{\n  \"name\": \"PyTorch GPU Template\",\n  \"image\": \"runpod/pytorch:2.8.0-py3.11-cuda12.8.1\",\n  \"category\": \"NVIDIA\",\n  \"disk\": 50,\n  \"ports\": [\n    \"8888/http\"\n  ],\n  \"env\": {\n    \"JUPYTER_ENABLE_LAB\": \"yes\"\n  },\n  \"mounts\": {\n    \"persistent\": {\n      \"size\": 20,\n      \"path\": \"/workspace\"\n    }\n  },\n  \"serverless\": false,\n  \"public\": false\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.runpod.io/v2/templates")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"PyTorch GPU Template\",\n  \"image\": \"runpod/pytorch:2.8.0-py3.11-cuda12.8.1\",\n  \"category\": \"NVIDIA\",\n  \"disk\": 50,\n  \"ports\": [\n    \"8888/http\"\n  ],\n  \"env\": {\n    \"JUPYTER_ENABLE_LAB\": \"yes\"\n  },\n  \"mounts\": {\n    \"persistent\": {\n      \"size\": 20,\n      \"path\": \"/workspace\"\n    }\n  },\n  \"serverless\": false,\n  \"public\": false\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.runpod.io/v2/templates")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"PyTorch GPU Template\",\n  \"image\": \"runpod/pytorch:2.8.0-py3.11-cuda12.8.1\",\n  \"category\": \"NVIDIA\",\n  \"disk\": 50,\n  \"ports\": [\n    \"8888/http\"\n  ],\n  \"env\": {\n    \"JUPYTER_ENABLE_LAB\": \"yes\"\n  },\n  \"mounts\": {\n    \"persistent\": {\n      \"size\": 20,\n      \"path\": \"/workspace\"\n    }\n  },\n  \"serverless\": false,\n  \"public\": false\n}"

response = http.request(request)
puts response.read_body

201

{
  "id": "9x4m2p7v",
  "name": "PyTorch GPU Template",
  "image": "runpod/pytorch:2.8.0-py3.11-cuda12.8.1",
  "args": "",
  "disk": 50,
  "mounts": {
    "persistent": {
      "size": 20,
      "path": "/workspace"
    }
  },
  "ports": [
    "8888/http"
  ],
  "env": {
    "JUPYTER_ENABLE_LAB": "yes"
  },
  "registry": null,
  "serverless": false,
  "public": false,
  "category": "NVIDIA"
}

{
  "title": "Bad Request",
  "status": 400,
  "detail": "request could not be processed"
}

{
  "title": "Unauthorized",
  "status": 401,
  "detail": "missing bearer token"
}

{
  "title": "Forbidden",
  "status": 403,
  "detail": "access denied"
}

{
  "title": "Unprocessable Entity",
  "status": 422,
  "detail": "Request validation failed."
}

{
  "title": "Too Many Requests",
  "status": 429,
  "detail": "rate limit exceeded for the minute window"
}

{
  "title": "<string>",
  "status": 123,
  "detail": "<string>",
  "errors": [
    "<string>"
  ]
}

Authorizations

Authorization · string · header · required

Runpod API key authentication. Generate an API key in the Runpod console and send it in the Authorization header as Bearer <api_key>. Keys are scoped to the permissions granted when created; requests may return 403 when a valid key lacks access to the requested resource or action.

Body

application/json

Reusable container configuration shared across templates, pods, and serverless endpoints. Adding a field here automatically propagates to all three resources.

image · string · required

Docker image reference

Example:

"runpod/pytorch:2.8.0-py3.11-cuda12.8.1"

name · string · required

Minimum string length: 1

Example:

"My PyTorch Template"

args · string

Arguments passed to the container entrypoint

Example:

""

disk · integer

Container disk in GB (ephemeral, wiped on restart)

Required range: x >= 1

Example:

50

ports · string[]

Exposed ports, formatted as port/protocol

Example:

["8888/http", "22/tcp"]

env · object

Environment variables as key-value pairs

Show child attributes

Example:

{ "JUPYTER_PASSWORD": "hunter2" }

registry · string | null

Container registry credential ID (for private images)

Example:

null

mounts · object

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.

Show child attributes

serverless · boolean · default: false

public · boolean · default: false

category · enum<string> · default: NVIDIA

Optional. Defaults to NVIDIA when omitted.

Available options: CPU, NVIDIA, AMD

Response

201

application/json

Created

Reusable container configuration shared across templates, pods, and serverless endpoints. Adding a field here automatically propagates to all three resources.

image · string · required

Docker image reference

Example:

"runpod/pytorch:2.8.0-py3.11-cuda12.8.1"

args · string · required

Arguments passed to the container entrypoint

Example:

""

disk · integer · required

Container disk in GB (ephemeral, wiped on restart)

Required range: x >= 1

Example:

50

ports · string[] · required

Exposed ports, formatted as port/protocol

Example:

["8888/http", "22/tcp"]

env · object · required

Environment variables as key-value pairs

Show child attributes

Example:

{ "JUPYTER_PASSWORD": "hunter2" }

registry · string | null · required

Container registry credential ID (for private images)

Example:

null

id · string · required

Example:

"tpl_abc"

name · string · required

Example:

"My PyTorch Template"

mounts · object · required

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.

Show child attributes

serverless · boolean · required

Whether this template is for serverless workers (true) or pods (false)

Example:

false

public · boolean · required

Whether this template is visible to other Runpod users

Example:

false

category · enum<string> · required

Controls how the template is grouped and filtered in the Runpod console. It does not affect hardware selection, scheduling, or billing.

• CPU — CPU-only workloads
• NVIDIA — NVIDIA GPU workloads
• AMD — AMD GPU workloads

Available options: CPU, NVIDIA, AMD