# Perplexity — Contextual embedding beyond the gold passage

- Company: Perplexity (perplexity.ai)
- Announced: 2026-09-30
- Category: new-model
- Coverage: not counted
- Announcement: yes
- Group: models
- Source: https://www.perplexity.ai/hub/blog/contextual-embedding-beyond-the-gold-passage
- Record: https://forck.live/items/15439-contextual-embedding-beyond-the-gold-passage
- Subject: Perplexity
- Open weights: yes
- Models affected: pplx-embed-v2-context-9b-preview

Perplexity released pplx-embed-v2-context-9b-preview, a contextual embedding model preview on Hugging Face. It uses a context compression model as a teacher to train chunk-level relevance scores, aiming to retrieve both answer chunks and supporting context instead of a single gold chunk. The model achieves state-of-the-art results on context-bench and ConTEB benchmarks.

## Evidence

Verbatim from https://www.perplexity.ai/hub/blog/contextual-embedding-beyond-the-gold-passage:

> We’re introducing pplx-embed-v2-context-9b-preview , our new contextual embedding model. The model is trained with a novel approach that uses Perplexity’s context compression model as a teacher. We aggregate its token-level predictions into chunk-level relevance scores, teaching the embedding model to retrieve both answer chunks and supporting context rather than a single gold chunk.

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Record: https://forck.live/items/15439-contextual-embedding-beyond-the-gold-passage
Catalogue: https://forck.live/llms.txt
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