Perplexity Embeddings

https://docs.perplexity.ai/docs/embeddings/quickstart

LiteLLM supports Perplexity's pplx-embed embedding models for web-scale text retrieval.

API Key

# env variable
os.environ['PERPLEXITYAI_API_KEY']

Sample Usage - Embedding

SDK

from litellm import embedding
import os

os.environ['PERPLEXITYAI_API_KEY'] = ""

response = embedding(
    model="perplexity/pplx-embed-v1-0.6b",
    input=["good morning from litellm"],
)
print(response)

Proxy

1. Setup config.yaml

model_list:
  - model_name: pplx-embed-v1-0.6b
    litellm_params:
      model: perplexity/pplx-embed-v1-0.6b
      api_key: os.environ/PERPLEXITYAI_API_KEY
  - model_name: pplx-embed-v1-4b
    litellm_params:
      model: perplexity/pplx-embed-v1-4b
      api_key: os.environ/PERPLEXITYAI_API_KEY

2. Start proxy

litellm --config /path/to/config.yaml

3. Test it!

curl http://0.0.0.0:4000/v1/embeddings \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-1234" \
  -d '{
    "model": "pplx-embed-v1-0.6b",
    "input": ["good morning from litellm"]
  }'

Supported Parameters

Perplexity embeddings support the following optional parameters:

Parameter	Type	Description
dimensions	int	Output embedding dimensions. 128–1024 for 0.6b models, 128–2560 for 4b models. Defaults to max.
encoding_format	string	"base64_int8" (default) or "base64_binary" for compressed output.

Example with Parameters

SDK

from litellm import embedding
import os

os.environ['PERPLEXITYAI_API_KEY'] = ""

response = embedding(
    model="perplexity/pplx-embed-v1-4b",
    input=["Your text here"],
    dimensions=512,
)
print(f"Embedding dimensions: {len(response.data[0]['embedding'])}")

Proxy

curl http://0.0.0.0:4000/v1/embeddings \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-1234" \
  -d '{
    "model": "pplx-embed-v1-4b",
    "input": ["Your text here"],
    "dimensions": 512
  }'

Supported Models

All models listed on the Perplexity Embeddings docs are supported. Use model=perplexity/<model-name>.

Model Name	Dimensions	Max Tokens	Price (per 1M tokens)	Function Call
pplx-embed-v1-0.6b	1024	32K	$0.004	embedding(model="perplexity/pplx-embed-v1-0.6b", input)
pplx-embed-v1-4b	2560	32K	$0.03	embedding(model="perplexity/pplx-embed-v1-4b", input)

Key Specifications

• Max texts per request: 512
• Max tokens per input: 32,768
• Combined request limit: 120,000 tokens
• Matryoshka dimension reduction — reduce dimensions to 128+ for faster search and reduced storage
• No instruction prefix required — embed text directly
• Unnormalized embeddings — use cosine similarity for comparison