> ## Documentation Index
> Fetch the complete documentation index at: https://langwatch.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# POST /v1/embeddings

> OpenAI-compatible embeddings endpoint through the LangWatch AI Gateway.

OpenAI-compatible embeddings. Works against OpenAI, Azure OpenAI, Bedrock (Titan), Vertex, Gemini, and Custom OpenAI-compatible providers that implement `/v1/embeddings`.

## Request

```
POST /v1/embeddings
Authorization: Bearer vk-lw-<ULID>
Content-Type: application/json
```

```json theme={null}
{
  "model": "text-embedding-3-small",
  "input": ["Hello", "World"]
}
```

`input` accepts a single string or an array of strings. Token pricing is per-input-token summed across the array.

## Response

OpenAI-shape. Additional LangWatch headers:

```http theme={null}
X-LangWatch-Request-Id: grq_01HZX9K3M...
X-LangWatch-Provider: openai
X-LangWatch-Model: text-embedding-3-small

{
  "object": "list",
  "data": [
    { "object": "embedding", "index": 0, "embedding": [0.012, -0.033, ...] },
    { "object": "embedding", "index": 1, "embedding": [0.089, 0.041, ...] }
  ],
  "model": "text-embedding-3-small",
  "usage": { "prompt_tokens": 2, "total_tokens": 2 }
}
```

## Provider compatibility

| Provider                 | Supported           | Models                                                                       |
| ------------------------ | ------------------- | ---------------------------------------------------------------------------- |
| OpenAI                   | ✅                   | `text-embedding-3-small`, `text-embedding-3-large`, `text-embedding-ada-002` |
| Azure OpenAI             | ✅                   | Same as OpenAI (via deployment names)                                        |
| Bedrock                  | ✅ Titan             | `amazon.titan-embed-text-v2:0`                                               |
| Vertex AI                | ✅ Gemini embeddings | `textembedding-gecko`, `gemini-embedding-001`                                |
| Gemini (AI Studio)       | ✅                   | `text-embedding-004`, `gemini-embedding-001`                                 |
| Anthropic                | ❌                   | No embeddings endpoint                                                       |
| Custom OpenAI-compatible | varies              | depends on upstream                                                          |

## Fallback and caching

Subject to the same fallback rules as chat (see [Fallback Chains](/docs/ai-gateway/providers/fallback-chains)). Embedding models are less prone to provider outages than chat models but the chain is there if needed.

Caching: deterministic, identical `(model, input)` tuples produce identical vectors, so aggressive semantic caching is feasible. V1 does not enable gateway-level caching for embeddings; use a local cache in your application layer.

## Errors

See [API: Errors](/docs/ai-gateway/api/errors).