lightonai/OriOn-Mistral
VISIONConcurrency Cost:2Model Size:24BQuant:FP8Ctx Length:32kPublished:Feb 7, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Cold

OriOn-Mistral by LightOn is a 24 billion parameter Mistral-based language model, fine-tuned for long-context visual document understanding and text long-context capabilities. It achieves strong gains in PDF VQA and multi-page reasoning, supporting a 344K context length with training on documents up to 336 pages. This model is optimized for tasks requiring deep comprehension of extensive visual and text documents.

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OriOn-Mistral: Long-Context Visual Document and Text Understanding

OriOn-Mistral is a 24 billion parameter model developed by LightOn, based on the Mistral-Small-3.1-24B-Instruct architecture. It has been specifically trained using CPT (Contextualized Pre-training) and SFT (Supervised Fine-Tuning) on synthetic data to excel in long-context visual document performance (such as PDF VQA and multi-page reasoning) and significantly boost text long-context capabilities.

Key Capabilities and Features

  • Extended Context Length: Supports an impressive 344K context length, trained on documents up to 336 pages, making it suitable for processing very long inputs.
  • Visual Document Understanding: Achieves substantial gains in long-document VQA, scoring 46.6 on MMLongBenchDoc (+16.8% compared to baseline).
  • Text Long-Context Performance: Demonstrates strong improvements in text long-context tasks, with a score of 53.1 on HELMET (+43.5% compared to baseline).
  • Reproducibility: Training recipes and ablations are available via the OriOn-Leaderboard.
  • Efficient Serving: Designed for drop-in serving with vLLM.

Intended Use Cases

OriOn-Mistral is particularly well-suited for applications requiring:

  • Long PDF / slide-deck QA and understanding: Performing one-shot question answering over entire documents.
  • Complex long-context reasoning: Leveraging its visual and text long-context training for enhanced reasoning across extensive materials.