Large Tabular Models Excel Where LLMs Fail
IEEE Spectrum AI Benjamin Skuse
Large tabular models (LTMs) are a new class of AI foundation models designed to handle structured data in spreadsheets, where traditional LLMs fail due to their sequential nature and lack of deterministic outputs. Fundamental launched its LTM called NEXUS on February 5, 2026, with $275 million in funding and achieved adoption by Amazon Web Services, with competitors including Google's TabFM and research models like FlexTab also emerging. This shifts enterprise data analysis away from legacy machine learning algorithms like XGBoost toward pre-trained foundational models that require minimal task-specific engineering.
Why it matters
The large language models (LLMs) that form the basis of generative AI chatbots such as ChatGPT, Claude, and Gemini can generate uncannily human-like text and images. But these models still struggle with a skill that, ironically, looks at face value to be right in their wheelhouse: analyzing structured data. A new type of generative AI is set to change this situation.Although you can get your favorite chatbot to solve intractable math problems, review dense legal documents, compose a catchy pop song, or put together some slick PowerPoint slides, give it anything more than a small table and it doesn’t have a clue what to do.For most companies and organizations, the most important data sits in spreadsheets. Whether it’s a bank’s transaction logs, a marketing agency’s website metrics, clinical trial participants’ vital signs, or the vast amount of proton collision information produced at atom smashers like the Large Hadron Collider, structured, row-and-column data runs the world, and LLMs
