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pplx embed context v1 4B

pplx-embed-context-v1-4B is a contextual embedding model for retrieval-augmented generation (RAG) pipelines, where document chunks benefit from awareness of surrounding content. Part of the pplx-embed-v1 family alongside standard dense embedding variants. Built on Qwen3 with diffusion-based continued pretraining, it produces 2560-dimensional embeddings with Matryoshka Representation Learning (MRL) support, enabling flexible dimensionality reduction. Natively quantizes to INT8 or binary formats for efficient retrieval. Supports a 32K token context window and multilingual input. Unlike most embedding models, it does not require instruction prefixes, simplifying indexing pipelines. Available via the Perplexity AI API at the /v1/contextualizedembeddings endpoint or self-hosted via Transformers or ONNX. Released under the MIT license.
Text Gen 7
Released: February 11, 2026

Overview

A 4B-parameter contextual text embedding model built on diffusion-pretrained Qwen3, designed for RAG pipelines where document chunks benefit from surrounding context. Produces 2560-dimensional INT8/BINARY-quantized embeddings with a 32K context window and MRL support. No instruction prefixes required. MIT-licensed with open weights.

Pricing

Compare pplx embed context v1 4B with other models listed in the same vendor pricing tiers and context lengths.

Embeddings

About Perplexity

Perplexity is a technology company that specializes in artificial intelligence and machine learning solutions.

Industry: Artificial Intelligence
Company Size: 247
Location: San Francisco, California, US
View Company Profile
Last updated: June 25, 2026
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