# Linkup Research releases sparseup 149M-parameter sparse embedding model

Digest AI · Generative AI & Models · published 2026-09-19T07:48:38Z

Canonical: https://digestai.news/story/linkup-research-releases-sparseup-149m-parameter-sparse-embedding-mode

## Summary

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 can be loaded via Transformers or Sentence‑Transformers with the appropriate flag. It incorporates three engineering fixes – a logit shift of 15, per‑position top‑12 token expansion, and case folding – to keep vectors sparse and human‑readable.

SPARSEUP scores 56.4 nDCG@10 on the BEIR‑13 benchmark, which Linkup claims is the strongest public vocabulary‑based sparse encoder under 150 M parameters. In the same controlled setting LateOn scores 58.9 and DenseOn 57.9. On MS MARCO the model attains over 97 % recall in roughly 380 µs per query (single‑threaded), with an average of 47 non‑zero terms per query and 190 per document. Training fits on a single H100 GPU and uses LightOn’s fine‑tuning mixture with contrastive learning.

## Key points

- SPARSEUP is a 149M‑parameter sparse encoder released under Apache 2.0 on Hugging Face.
- It achieves 56.4 nDCG@10 on BEIR‑13, the highest among public sparse models under 150M parameters.
- On MS MARCO it reaches >97% recall in ~380 µs per query with 47 and 190 non‑zero terms.

## Why it matters

An open, efficient sparse encoder lets developers build fast, interpretable retrieval systems without large dense vectors, lowering compute costs and latency for search‑heavy applications.

## Sources

1. [Linkup Research Releases SPARSEUP: A 149M-Parameter Open-Source Sparse Embedding Model](https://marktechpost.com/2026/09/19/linkup-research-releases-sparseup) (MarkTechPost, 2026-09-19)

## Cite

Digest AI, "Linkup Research releases sparseup 149M-parameter sparse embedding model", 19 September 2026, https://digestai.news/story/linkup-research-releases-sparseup-149m-parameter-sparse-embedding-mode

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