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[P] ColQwen3.5-v1 4.5B SOTA on ViDoRe V1 (nDCG@5 0.917)

Reddit r/MachineLearning / 3/11/2026

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Key Points

  • ColQwen3.5-v1 is a 4.5 billion parameter model built upon Qwen3.5-4B using the ColPali late-interaction approach.
  • It currently ranks #1 on the ViDoRe V1 benchmark with an nDCG@5 score of 0.917 and is competitive on ViDoRe V3.
  • The model was trained in four phases, including hard negative mining and domain specialization for finance and table document data.
  • The model weights are available on Hugging Face under an Apache 2.0 license, and a pull request to merge the code into the ColPali repository is underway.
  • The developer is working on a version 2 to simplify the training process and extend coverage to more domains, aiming to achieve state-of-the-art results on ViDoRe V3 soon.

Sharing a model I've been working on: ColQwen3.5-v1, a 4.5B param model built on Qwen3.5-4B using the ColPali late-interaction approach.

Currently #1 on ViDoRe V1 (nDCG@5 0.917) & competitive on ViDoRe V3. Trained across 4 phases including hard negative mining and domain specialization on finance/table docs.

Apache 2.0, weights on HF: https://huggingface.co/athrael-soju/colqwen3.5-v1 & PR raised to merge in https://github.com/illuin-tech/colpali

Working on v2 to simplify the training recipe & cover more domains, with the aim of reaching SOTA #1 on ViDoRe V3 soon.

Let me know if you try it out!

submitted by /u/madkimchi
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