Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance

Falcon-Edge: A series of powerful, universal, fine-tunable 1.58bit language models.

Component Ablation for Efficient Hybrid Language Model Architectures: Performance, Resilience, and Compression Implications

arXiv:2603. 22473v2 Announce Type: replace-cross Abstract: Hybrid language models combine softmax attention with linear-time sequence mechanisms such as state-space or linear-attention layers, but the functional contribution of each component type remains insufficiently characterized.

Falcon 2: An 11B parameter pretrained language model and VLM, trained on over 5000B tokens and 11 languages

Introducing Falcon-H1-Arabic: Pushing the Boundaries of Arabic Language AI with Hybrid Architecture

Falcon-Arabic: A Breakthrough in Arabic Language Models

Large Language Models: A New Moore's Law?