Overview
BLOOM (BigScience Large Open-science Open-access Multilingual Language Model) is a 176-billion parameter autoregressive large language model, trained on the Jean Zay supercomputer in France. Developed by the BigScience workshop—a global collaboration of over 1,000 researchers—BLOOM represents a landmark in AI transparency and democratization. Architecturally, it is a decoder-only Transformer model incorporating ALiBi positional embeddings, which allow for better context handling than traditional sinusoidal embeddings. It supports 46 natural languages and 13 programming languages, making it one of the most linguistically diverse open models available in 2026. As an open-access model, it enables researchers and enterprises to inspect the weights, training data, and intermediate results, offering a level of auditability often missing in proprietary models like GPT-4. In the 2026 landscape, BLOOM serves as a foundational pillar for organizations prioritizing data sovereignty and customized on-premise deployments, particularly in regions where low-resource languages are prevalent. While newer iterations like BLOOMZ offer instruction-tuned capabilities, the base BLOOM model remains a core benchmark for evaluating large-scale cross-lingual transfer learning and ethical AI development.