# Embeddings API Pricing

As of October 10, 2026, Embeddings is free to use on GigaChat. It has a 512-token context window.

- Page: https://models.litellm.ai/models/embeddings
- LiteLLM model name: `gigachat/Embeddings`
- Context window: 512 tokens
- Added to LiteLLM: January 2026
- Prices updated: October 10, 2026

## Pricing by provider

Token prices in USD per 1M tokens.

| Provider | Model name | Input | Output | Cache read | Per image | Per second | Context |
|---|---|---|---|---|---|---|---|
| GigaChat | `gigachat/Embeddings` | $0 | $0 | – | – | – | 512 |

## Cost examples

Embedding 10,000 documents of 500 tokens each:

- GigaChat: $0

## Use it with LiteLLM

```python
from litellm import embedding

response = embedding(
    model="gigachat/Embeddings",
    input=["hello world"],
)
```

## FAQ

### How much does Embeddings cost?

Embeddings is free to use on GigaChat.

### What is the context window of Embeddings?

Embeddings has a 512-token context window.

### Which providers offer Embeddings?

Embeddings is available from GigaChat through LiteLLM, using the model name gigachat/Embeddings.

### How do I call Embeddings with an OpenAI-compatible API?

Use the LiteLLM Python SDK with model="gigachat/Embeddings", or add the model to the LiteLLM proxy's config.yaml and send requests to /v1/embeddings from any OpenAI client. LiteLLM tracks the cost of every request at the prices on this page.

### When did LiteLLM add Embeddings?

Embeddings was added to LiteLLM's model price file in January 2026.

Source: LiteLLM model price file, https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json