LightOn said its open-source GTE-ModernColBERT beat the best existing models by 10 points on long documents in LongEmbed, May 7, 2025
LightOn released the multi-vector retrieval model under the Apache 2.0 licence and said it handled documents of up to 32,000 tokens.
LightOn said on May 7, 2025 that it had released GTE-ModernColBERT, an open-source multi-vector retrieval model. A retrieval model is the search step that finds relevant passages for AI-generated answers, as in retrieval-augmented generation (RAG); the release said the model enabled more accurate retrieval for such responses. The release contrasted multi-vector models with single-vector embedding models, which it said had become standard in the industry.1,2,3,4
The company said the model outperformed other models in the field, among them those of Alibaba, Snowflake, Cohere, BAAI and JinaAI, on LongEmbed, a benchmark it called industry-standard. It put the lead over the best existing models at a 10 point margin on documents of up to 32,000 tokens, which the release equated to texts of dozens of pages, even though the model was first trained only on 300 token excerpts from the MS MARCO dataset. LightOn also listed as a benefit that it was the first model to surpass ColBERT-small on the BEIR benchmark.5,6,7
LightOn said it created the model by leveraging the ModernBERT architecture, which it said it built, and its PyLate library, a framework for training multi-vector retrieval models that it said needed only 80 lines of code to reproduce the training. It said that training on MS MARCO by knowledge distillation produced a lightweight model that does not compromise on performance. The release added that most major vector databases, among them QDrant, LanceDB, Weaviate and Vespa, supported multi-vector indexing.8,9,10,11,12
The release said the model was released under an Apache 2.0 licence and that PyLate was open source as well, and it pointed readers to Hugging Face to try the model. LightOn describes itself as founded in 2016 in Paris and as the first European generative AI company listed on Euronext Growth.13,14,15
The text we hold is the release in English; the AMF also lists a French record of the same day. The results are LightOn's own, and the text we hold does not state which measure the 10 point margin is expressed in.16,17,18,6
How each figure was checked
- date LightOn's release was published through the AMFMay 7, 2025
- LightOn announces the release of GTE-ModernColBERT, a state-of-the-art open-source multi-vector retrieval modelLightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- the release says the model is for retrieval-augmented generation, enabling more accurate retrieval for AI-generated responsesLightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- the release says single-vector embedding models have become standard in the industryLightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- LightOn says the model outperforms models of Alibaba, Snowflake, Cohere, BAAI and JinaAI on the LongEmbed benchmarkLightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- LightOn says the model beats the best existing models by a 10 point margin on LongEmbed, on documents up to 32,000 tokens, though first trained on 300 token excerpts of MS MARCO10 point margin on LongEmbed; documents up to 32,000 tokens; 300 token excerptsLightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- LightOn lists as a benefit being the first model to surpass ColBERT-small on the BEIR benchmarkLightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- LightOn says the model leverages the ModernBERT architecture and its PyLate libraryLightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- LightOn says it built ModernBERT to enable powerful retrieval modelsLightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- LightOn says it built PyLate, a framework for training multi-vector retrieval models, and only 80 lines of code are needed to reproduce the training80 lines of codeLightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- LightOn says it trained on MS MARCO by knowledge distillation to make a lightweight model that does not compromise on performanceLightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- LightOn says most major vector databases including QDrant, LanceDB, Weaviate and Vespa now support multi-vector indexationLightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- the model is released as an Apache 2.0 licensed open-source solution, and PyLate is open-sourcedApache 2.0LightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- the release tells readers to try the model on Hugging FaceLightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- LightOn says it was founded in 2016 in Paris and is the first European generative AI company listed on Euronext Growth2016LightOn press release, AMF regulated information, in English (May 7, 2025) ↗
- language of the stored text of the releaseEnglish
- title of the AMF's French record of the same day
- what our records hold of the release
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The record
- Company
- LightOn (LEI 9695002GVC14VHLFIH85)
- ISIN
- FR0013230950
- Filed as
- Informations privilégiées
- Title (English)
- LightOn sets new standards for complex information retrieval (RAG) with GTEModernColBERT.
- Published
- May 7 · 15:46 UTC
- Title (French)
- LightOn redéfinit les standards de la recherche d’information complexe (RAG) avec GTEModernColBERT.
- Published
- May 7 · 15:46 UTC
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