AI Embedding Race Heats Up
The saga follows the rapid emergence of new AI embedding models, beginning with Linkup Research's release of the 149‑million‑parameter sparseup model and continuing with Perplexity and turbopuffer's launch of the larger pplx‑embed‑v2‑context‑9b‑preview. The story now stands at a competitive phase where larger, more capable embeddings are being introduced, signaling an accelerating push for efficient, high‑performance AI representations.
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Perplexity and turbopuffer release pplx-embed-v2-context-9b-preview embedding model
Perplexity Research and turbopuffer have launched a preview of their new contextual embedding model, pplx-embed-v2-context-9b-preview. The 9‑billion‑parameter model is available as self‑hosted…
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Linkup Research releases sparseup 149M-parameter sparse embedding model
Linkup Research announced SPARSEUP, an open‑source sparse embedding model built on a 149 million‑parameter ModernBERT backbone. The model is released under the Apache 2.0 license on Hugging Face and…
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