# 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 'Authorization: Bearer <token>'
```

```json title="200"
{
  "models": [
    {
      "model": "multilingual-e5-large",
      "short_description": "multilingual-e5-large",
      "type": "embed",
      "vector_type": "<string>",
      "default_dimension": 1024,
      "modality": "text",
      "max_sequence_length": 512,
      "max_batch_size": 96,
      "provider_name": "NVIDIA",
      "supported_dimensions": [
        1024
      ],
      "supported_metrics": [
        null
      ],
      "supported_parameters": [
        null
      ]
    }
  ]
}
```
:::

## Authorizations

- `Authorization` (header, string, required) — Bearer authentication header of the form `Bearer <token>`.

## Query Parameters

- `type` (query, string) — Filter models by type ('embed' or 'rerank').
- `vector_type` (query, string) — Filter embedding models by vector type ('dense' or 'sparse'). Only relevant when `type=embed`.

## Headers

- `X-Pinecone-Api-Version` (header, string, required) — Required date-based version header

## Response

- `200` — The list of available models.
- `401` — Unauthorized. Possible causes: Invalid API key.
- `404` — Model not found.
- `500` — Internal server error.

## Related pages

- [Generate vectors](./inference-2026-07-generate-vectors.md)
- [Rerank results](./inference-2026-07-rerank-results.md)
- [Describe a model](./inference-2026-07-describe-a-model.md)

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