{"ID":2844893,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.08621","arxiv_id":"2511.08621","title":"The LLM Pro Finance Suite: Multilingual Large Language Models for Financial Applications","abstract":"The financial industry's growing demand for advanced natural language processing (NLP) capabilities has highlighted the limitations of generalist large language models (LLMs) in handling domain-specific financial tasks. To address this gap, we introduce the LLM Pro Finance Suite, a collection of five instruction-tuned LLMs (ranging from 8B to 70B parameters) specifically designed for financial applications. Our approach focuses on enhancing generalist instruction-tuned models, leveraging their existing strengths in instruction following, reasoning, and toxicity control, while fine-tuning them on a curated, high-quality financial corpus comprising over 50% finance-related data in English, French, and German. We evaluate the LLM Pro Finance Suite on a comprehensive financial benchmark suite, demonstrating consistent improvement over state-of-the-art baselines in finance-oriented tasks and financial translation. Notably, our models maintain the strong general-domain capabilities of their base models, ensuring reliable performance across non-specialized tasks. This dual proficiency, enhanced financial expertise without compromise on general abilities, makes the LLM Pro Finance Suite an ideal drop-in replacement for existing LLMs in financial workflows, offering improved domain-specific performance while preserving overall versatility. We publicly release two 8B-parameters models to foster future research and development in financial NLP applications: https://huggingface.co/collections/DragonLLM/llm-open-finance.","short_abstract":"The financial industry's growing demand for advanced natural language processing (NLP) capabilities has highlighted the limitations of generalist large language models (LLMs) in handling domain-specific financial tasks. To address this gap, we introduce the LLM Pro Finance Suite, a collection of five instruction-tuned...","url_abs":"https://arxiv.org/abs/2511.08621","url_pdf":"https://arxiv.org/pdf/2511.08621v1","authors":"[\"Gaëtan Caillaut\",\"Raheel Qader\",\"Jingshu Liu\",\"Mariam Nakhlé\",\"Arezki Sadoune\",\"Massinissa Ahmim\",\"Jean-Gabriel Barthelemy\"]","published":"2025-11-07T11:08:31Z","proceeding":"q-fin.ST","tasks":"[\"q-fin.ST\",\"cs.AI\",\"q-fin.CP\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}