LiteLLMModels

Embeddings API Pricing

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

Model ID gigachat/EmbeddingsPrices updated Checked
Price
Free
Context window
512 tokens
Providers
1
Added to LiteLLM
January 2026

Embeddings pricing by provider

1 listing across 1 provider. Token prices are in US dollars per 1M tokens. The highlighted row is the price quoted above.

ProviderModel name in LiteLLMInputOutputContext
GigaChatgigachat/Embeddings$0$0512

What Embeddings costs in practice

Embedding 10,000 documents of 500 tokens each

GigaChat$0

Use Embeddings with LiteLLM

Call Embeddings through the LiteLLM Python SDK, or put it behind the LiteLLM proxy and send OpenAI-format requests to /v1/embeddings. LiteLLM tracks the cost of every request at these prices.

Python SDK
from litellm import embedding

response = embedding(
    model="gigachat/Embeddings",
    input=["hello world"],
)
Proxy config.yaml
model_list:
  - model_name: embeddings
    litellm_params:
      model: gigachat/Embeddings
      # credentials: see the provider's LiteLLM docs page
Call the proxy
curl http://0.0.0.0:4000/v1/embeddings \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-1234" \
  -d '{
    "model": "embeddings",
    "input": "hello world"
  }'

Embeddings 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.

Sources

Prices come from LiteLLM's open-source model_prices_and_context_window.json, which LiteLLM uses to calculate the cost of every request.

LiteLLM docs: GigaChat.

Provider pages: GigaChat.