pplx-embed-v2-context-9b-preview
A 9-billion-parameter contextual embedding model released by Perplexity that dynamically adjusts vector representations based on the overall context of a document. It is designed for retrieval optimization in RAG systems.
Timeline (last 90 days)
Perplexity has launched the preview model pplx-embed-v2-context-9b-preview.
pplx-embed-v2-context-9b-preview has achieved state-of-the-art (SOTA) results on two benchmarks: ConTEB and context-bench.
The pplx-embed-v2-context-9b model has approximately 9 billion (9B) parameters, which is a relatively large scale for an embedding model.
The model is currently released as a preview version; information comes primarily from an official brief announcement, and independent third-party replication and cross-benchmarking are not yet available.
pplx-embed-v2-context-9b-preview is a contextual embedding model with 9 billion parameters.
pplx-embed-v2-context-9b-preview achieved best-in-class performance on both the ConTEB and turbopuffer context-bench benchmarks (official data).
All Facts (6)
pplx-embed-v2-context-9b-preview has achieved state-of-the-art (SOTA) results on two benchmarks: ConTEB and context-bench.
50%UnverifiedThe pplx-embed-v2-context-9b model has approximately 9 billion (9B) parameters, which is a relatively large scale for an embedding model.
50%UnverifiedThe model is currently released as a preview version; information comes primarily from an official brief announcement, and independent third-party replication and cross-benchmarking are not yet available.
50%Unverifiedpplx-embed-v2-context-9b-preview is a contextual embedding model with 9 billion parameters.
50%Unverifiedpplx-embed-v2-context-9b-preview achieved best-in-class performance on both the ConTEB and turbopuffer context-bench benchmarks (official data).
50%UnverifiedPerplexity has launched the preview model pplx-embed-v2-context-9b-preview.
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