Embeddings 2 API Pricing
As of October 10, 2026, Embeddings 2 is free to use on GigaChat. It has a 512-token context window.
- Price
- Free
- Context window
- 512 tokens
- Providers
- 1
- Added to LiteLLM
- January 2026
Embeddings 2 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.
| Provider | Model name in LiteLLM | Input | Output | Context |
|---|---|---|---|---|
| GigaChat | gigachat/Embeddings-2 | $0 | $0 | 512 |
What Embeddings 2 costs in practice
Embedding 10,000 documents of 500 tokens each
| GigaChat | $0 |
Use Embeddings 2 with LiteLLM
Call Embeddings 2 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.
from litellm import embedding
response = embedding(
model="gigachat/Embeddings-2",
input=["hello world"],
)model_list:
- model_name: embeddings-2
litellm_params:
model: gigachat/Embeddings-2
# credentials: see the provider's LiteLLM docs pagecurl http://0.0.0.0:4000/v1/embeddings \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-1234" \
-d '{
"model": "embeddings-2",
"input": "hello world"
}'Embeddings 2 FAQ
How much does Embeddings 2 cost?
Embeddings 2 is free to use on GigaChat.
What is the context window of Embeddings 2?
Embeddings 2 has a 512-token context window.
Which providers offer Embeddings 2?
Embeddings 2 is available from GigaChat through LiteLLM, using the model name gigachat/Embeddings-2.
How do I call Embeddings 2 with an OpenAI-compatible API?
Use the LiteLLM Python SDK with model="gigachat/Embeddings-2", 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 2?
Embeddings 2 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.
