---
title: "Perplexity Embeddings"
description: "import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';"
type: skill
canonical_url: https://claudary.paisolsolutions.com/skills/perplexity-embedding
source: "Claudary"
difficulty: intermediate
author: "Claude Code Knowledge Pack"
date: 2026-07-10T11:31:58.508Z
license: CC-BY-4.0
attribution: "Perplexity Embeddings — Claudary (https://claudary.paisolsolutions.com/skills/perplexity-embedding)"
---

# Perplexity Embeddings
import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';

## Overview

import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';

# Perplexity Embeddings

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

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

## API Key

```python
# env variable
os.environ['PERPLEXITYAI_API_KEY']
```

## Sample Usage - Embedding

<Tabs>
<TabItem value="sdk" label="SDK">

```python
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)
```

</TabItem>
<TabItem value="proxy" label="Proxy">

1. Setup config.yaml

```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

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

3. Test it!

```bash
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"]
  }'
```

</TabItem>
</Tabs>

## 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

<Tabs>
<TabItem value="sdk" label="SDK">

```python
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'])}")
```

</TabItem>
<TabItem value="proxy" label="Proxy">

```bash
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
  }'
```

</TabItem>
</Tabs>

## Supported Models

All models listed on the [Perplexity Embeddings docs](https://docs.perplexity.ai/docs/embeddings/quickstart) 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

---

Source: [Claudary](https://claudary.paisolsolutions.com/skills/perplexity-embedding) · https://claudary.paisolsolutions.com