Create a pod-based index

Pod-based indexes are legacy. Customers who signed up for a Standard or Enterprise plan on or after August 18, 2025 cannot create them. Create a serverless index instead. Serverless indexes use on-demand read capacity by default, or dedicated read nodes for sustained high query rates and workloads of millions of records or more.

SDKs that target API version 2026-07 don’t support creating pod-based indexes, and they reject creating an index from a collection. You can still list, describe, and delete existing collections. To create or restore a pod-based index, use an SDK version that targets an earlier API version, or send an earlier X-Pinecone-Api-Version with the REST API. To move a pod-based index to serverless, see Migrate a pod-based index to serverless.

This page shows you how to create a pod-based index. For guidance on serverless indexes, see Create a serverless index.

Create a pod index

To create a pod index, use the Create an index operation as follows:

Provide a name for the index.
Specify the dimension and metric of the vectors you’ll store in the index. This should match the dimension and metric supported by your embedding model.
Set spec.environment to the environment where the index should be deployed. For Python, you also need to import the ServerlessSpec class.
Set spec.pod_type to the pod type and size that you want.

Other parameters are optional. See the API reference for details.

from pinecone.grpc import PineconeGRPC as Pinecone, PodSpec

pc = Pinecone(api_key="YOUR_API_KEY")

pc.create_index(
  name="docs-example",
  dimension=1536,
  metric="cosine",
  spec=PodSpec(
    environment="us-west1-gcp",
    pod_type="p1.x1",
    pods=1
  ),
  deletion_protection="disabled"

)

import { Pinecone } from '@pinecone-database/pinecone'

const pc = new Pinecone({
  apiKey: 'YOUR_API_KEY'
});

await pc.createIndex({
  name: 'docs-example',
  dimension: 1536,
  metric: 'cosine',
  spec: {
    pod: {
      environment: 'us-west1-gcp',
      podType: 'p1.x1',
      pods: 1
    }
  },
  deletionProtection: 'disabled',
});

import io.pinecone.clients.Pinecone;
import org.openapitools.db_control.client.model.IndexModel;
import org.openapitools.db_control.client.model.DeletionProtection;

public class CreateIndexExample {
    public static void main(String[] args) {
        Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build();
        pc.createPodsIndex("docs-example", 1536, "us-west1-gcp",
                "p1.x1", "cosine", DeletionProtection.DISABLED);
    }
}

package main

import (
    "context"
    "fmt"
    "log"

    "github.com/pinecone-io/go-pinecone/v4/pinecone"
)

func main() {
    ctx := context.Background()

    pc, err := pinecone.NewClient(pinecone.NewClientParams{
        ApiKey: "YOUR_API_KEY",
    })
    if err != nil {
        log.Fatalf("Failed to create Client: %v", err)
    }

    indexName := "docs-example"
  	metric := pinecone.Dotproduct
	  deletionProtection := pinecone.DeletionProtectionDisabled

    idx, err := pc.CreatePodIndex(ctx, &pinecone.CreatePodIndexRequest{
        Name:               indexName,
        Metric:             &metric,
        Dimension:          1536,
        Environment:        "us-east1-gcp",
        PodType:            "p1.x1",
        DeletionProtection: &deletionProtection,
    })
    if err != nil {
        log.Fatalf("Failed to create pod-based index: %v", idx.Name)
    } else {
        fmt.Printf("Successfully created pod-based index: %v", idx.Name)
    }
}

PINECONE_API_KEY="YOUR_API_KEY"

curl -s "https://api.pinecone.io/indexes" \
  -H "Accept: application/json" \
  -H "Content-Type: application/json" \
  -H "Api-Key: $PINECONE_API_KEY" \
  -H "X-Pinecone-Api-Version: 2025-10" \
  -d '{
         "name": "docs-example",
         "dimension": 1536,
         "metric": "cosine",
         "spec": {
            "pod": {
               "environment": "us-west1-gcp",
               "pod_type": "p1.x1",
               "pods": 1
            }
         },
         "deletion_protection": "disabled"
      }'

Create a pod index from a collection

You can create a pod-based index from a collection. For more details, see Restore an index.

Get started

Core concepts

Index data

Search

Optimize

Manage data

Manage cost

Move to production

Admin

Operations

Using pods

Create a pod-based index

Create a pod index

Create a pod index from a collection

​Create a pod index

​Create a pod index from a collection

Create a pod index

Create a pod index from a collection