Falcon-H1-Tiny

Falcon-H1-Arabic

Technology Innovation Institute

Falcon-H1-Arabic is a TII open-weight language-model release. Falcon-H1-Arabic specializes the hybrid Falcon architecture for Arabic, dialects, and bilingual enterprise work. Continued training and post-training focus on long-context instruction following and Arabic linguistic quality. The 3B tier supports 128K context, while 7B and 34B support 256K; the family-level context shown describes the larger tiers. Published license terms and checkpoint-specific hardware needs apply. Generated text can contain unsupported claims; sparse computation, reduced precision, or hybrid sequence modeling does not remove the need for task evaluation.

Falcon-H1R

Technology Innovation Institute

Falcon-H1R is a TII open-weight language-model release. Falcon-H1R is the reasoning-specialized 7B hybrid model post-trained from Falcon-H1. It targets math, coding, and scientific reasoning with longer test-time computation and search options. Reported contest performance may use DeepConf or multiple candidates, and should not be interpreted as single-response accuracy. Published license terms and checkpoint-specific hardware needs apply. Generated text can contain unsupported claims; sparse computation, reduced precision, or hybrid sequence modeling does not remove the need for task evaluation.

Falcon-H1

Technology Innovation Institute

Falcon-H1 is a TII open-weight language-model release. Falcon-H1 replaces purely attention-based blocks with parallel attention and state-space heads. The family spans edge and larger enterprise sizes, including a deeper 1.5B variant. Model-specific head allocations and long-context training target efficient multilingual reasoning. Context capacity and language performance depend on size and serving configuration. Published license terms and checkpoint-specific hardware needs apply. Generated text can contain unsupported claims; sparse computation, reduced precision, or hybrid sequence modeling does not remove the need for task evaluation.