Skillintermediate

Perplexity Embeddings

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Claude Code Knowledge Pack7/10/2026

Overview

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

from litellm import embedding

os.environ['PERPLEXITYAI_API_KEY'] = ""

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

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

Start proxy

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

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

from litellm import embedding

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'])}")

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