# List available models

You can use hosted models as an integrated part of Pinecone operations or for standalone embedding and reranking. For more details, see [Vector embedding](/guides/index-data-indexing-overview#vector-embedding) and [Rerank results](/guides/index-data-search-rerank-results).

`GET /models`

:::code-group
```bash title="cURL"
curl --request GET \
  --url https://api.pinecone.io/models \
  --header 'Api-Key: <api-key>' \
  --header 'X-Pinecone-Api-Version: <x-pinecone-api-version>'
```

```python title="Python"
import requests

url = "https://api.pinecone.io/models"

headers = {
    "Api-Key": "<api-key>",
    "X-Pinecone-Api-Version": "<x-pinecone-api-version>"
}

response = requests.get(url, headers=headers)

print(response.text)
```

```javascript title="JavaScript"
const options = {method: "GET", headers: {"Api-Key": "<api-key>", "X-Pinecone-Api-Version": "<x-pinecone-api-version>"}};

fetch("https://api.pinecone.io/models", options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));
```

```php title="PHP"
<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.pinecone.io/models",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_CUSTOMREQUEST => "GET",
  CURLOPT_HTTPHEADER => [
    "Api-Key: <api-key>",
    "X-Pinecone-Api-Version: <x-pinecone-api-version>"
  ],
]);

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

curl_close($curl);

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

```go title="Go"
package main

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

func main() {

	url := "https://api.pinecone.io/models"

	req, _ := http.NewRequest("GET", url, nil)

	req.Header.Add("Api-Key", "<api-key>")
	req.Header.Add("X-Pinecone-Api-Version", "<x-pinecone-api-version>")

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

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

	fmt.Println(string(body))

}
```

```java title="Java"
HttpResponse<String> response = Unirest.get("https://api.pinecone.io/models")
  .header("Api-Key", "<api-key>")
  .header("X-Pinecone-Api-Version", "<x-pinecone-api-version>")
  .asString();
```

```ruby title="Ruby"
require 'uri'
require 'net/http'

url = URI("https://api.pinecone.io/models")

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

request = Net::HTTP::Get.new(url)
request["Api-Key"] = '<api-key>'
request["X-Pinecone-Api-Version"] = '<x-pinecone-api-version>'

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

:::code-group
```json title="200"
{
  "models": [
    {
      "default_dimension": 256,
      "max_batch_size": 96,
      "max_sequence_length": 512,
      "modality": "text",
      "model": "example-embedding-model",
      "provider_name": "Embedding Model Provider",
      "short_description": "An example embedding model.",
      "supported_dimensions": [
        256,
        512
      ],
      "supported_metrics": [
        "cosine",
        "euclidean"
      ],
      "supported_parameters": [
        {
          "allowed_values": [
            "value1",
            "value2"
          ],
          "parameter": "example_required_param",
          "required": true,
          "type": "one_of",
          "value_type": "string"
        },
        {
          "allowed_values": [
            "value1",
            "value2"
          ],
          "default": "value1",
          "parameter": "example_param_with_default",
          "required": false,
          "type": "one_of",
          "value_type": "string"
        },
        {
          "default": 5,
          "max": 10,
          "min": 0,
          "parameter": "example_numeric_range",
          "required": false,
          "type": "numeric_range",
          "value_type": "integer"
        }
      ],
      "type": "embed",
      "vector_type": "dense"
    },
    {
      "max_batch_size": 100,
      "max_sequence_length": 1024,
      "modality": "text",
      "model": "example-reranking-model",
      "provider_name": "Reranking Model Provider",
      "short_description": "An example reranking model.",
      "supported_parameters": [
        {
          "default": true,
          "parameter": "example_any_value",
          "required": false,
          "type": "any",
          "value_type": "boolean"
        }
      ],
      "type": "rerank"
    }
  ]
}
```

```json title="401"
{
  "error": {
    "code": "UNAUTHENTICATED",
    "message": "Invalid API key."
  },
  "status": 401
}
```

```json title="404"
{
  "error": {
    "code": "NOT_FOUND",
    "message": "Model example-model not found."
  },
  "status": 404
}
```

```json title="500"
{
  "error": {
    "code": "UNKNOWN",
    "message": "Internal server error"
  },
  "status": 500
}
```
:::

#### Authorizations

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `Api-Key` | `string` | - |  |

An API Key is required to call Pinecone APIs. Get yours from the [console](https://app.pinecone.io/).

#### Headers

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `X-Pinecone-Api-Version` | `string` | `2026-07` | Required date-based version header |

#### Query Parameters

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `type?` | `string` | - | Filter models by type ('embed' or 'rerank'). |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `vector_type?` | `string` | - | Filter embedding models by vector type ('dense' or 'sparse'). Only relevant when type=embed. |

#### Response

`200` — The list of available models.

The list of available models.

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `models?` | `object[]` | - | List of available models. |

::::accordion{title="Show child attributes"}
| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `model` | `string` | - | The name of the model. Example: multilingual-e5-large |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `short_description` | `string` | - | A summary of the model. Example: multilingual-e5-large |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `type` | `string` | - | The type of model (e.g. 'embed' or 'rerank'). Example: embed |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `vector_type?` | `string` | - | Whether the embedding model produces 'dense' or 'sparse' embeddings. |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `default_dimension?` | `integer` | - | The default embedding model dimension (applies to dense embedding models only). Required range: 1 <= x <= 20000. Example: 1024 |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `modality?` | `string` | - | The modality of the model (e.g. 'text'). Example: text |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `max_sequence_length?` | `integer` | - | The maximum tokens per sequence supported by the model. Required range: 1 <= x. Example: 512 |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `max_batch_size?` | `integer` | - | The maximum batch size (number of sequences) supported by the model. Required range: 1 <= x. Example: 96 |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `provider_name?` | `string` | - | The name of the provider of the model. Example: NVIDIA |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `supported_dimensions?` | `integer[]` | - | The list of supported dimensions for the model (applies to dense embedding models only). |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `supported_metrics?` | `string[]` | - | The distance metrics supported by the model for similarity search. |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `supported_parameters` | `object[]` | - | List of parameters supported by the model. |

:::accordion{title="Show child attributes"}
| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `parameter` | `string` | - | The name of the parameter. Example: input_type |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `type` | `string` | - | The parameter type e.g. 'one_of', 'numeric_range', or 'any'. If the type is 'one_of', then 'allowed_values' will be set, and the value specified must be one of the allowed values. 'one_of' is only compatible with value_type 'string' or 'integer'. If 'numeric_range', then 'min' and 'max' will be set, then the value specified must adhere to the value_type and must fall within the [min, max] range (inclusive). If 'any' then any value is allowed, as long as it adheres to the value_type. Example: one_of |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `value_type` | `string` | - | The type of value the parameter accepts, e.g. 'string', 'integer', 'float', or 'boolean'. Example: string |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `required` | `boolean` | - | Whether the parameter is required (true) or optional (false). Example: true |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `allowed_values?` | `string[]` | - | The allowed parameter values when the type is 'one_of'. |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `min?` | `number` | - | The minimum allowed value (inclusive) when the type is 'numeric_range'. Example: 1 |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `max?` | `number` | - | The maximum allowed value (inclusive) when the type is 'numeric_range'. Example: 1 |

| Prop | Type | Default | Description |
| --- | --- | --- | --- |
| `default?` | `string` | - |  |
:::
::::

## Related pages

- [Generate vectors](./inference-generate-vectors.md)
- [Rerank results](./inference-rerank-results.md)
- [Describe a model](./inference-describe-a-model.md)

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