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

- Company: TII (tii.ae)
- Announced: 2026-01-05T01:00:00+00:00
- Category: new-model
- Coverage: not counted
- Announcement: yes
- Group: models
- Source: https://falcon-lm.github.io/blog/falcon-h1-arabic/
- Record: https://forck.live/items/18413-introducing-falcon-h1-arabic-pushing-the-boundaries-of-arabic-language-ai-with
- Subject: Falcon LLM
- Models affected: Falcon-H1-Arabic, Falcon-H1-Arabic 3B, Falcon-H1-Arabic 7B, Falcon-H1-Arabic 34B
- Context window: 128K tokens for the 3B model and 256K tokens for both the 7B and 34B models

TII released Falcon-H1-Arabic, a family of Arabic language models (3B, 7B, 34B parameters) built on a hybrid Mamba-Transformer architecture. The models support context windows of up to 256K tokens and were trained on a mix of Arabic, English, and multilingual data totaling around 300 billion tokens. Post-training included supervised fine-tuning and direct preference optimization to improve long-context reasoning and alignment.

## Evidence

Verbatim from https://falcon-lm.github.io/blog/falcon-h1-arabic/:

> Falcon-H1-Arabic is built on the Falcon-H1 hybrid architecture, which integrates State Space Models (Mamba) and Transformer attention within every block. Both components run in parallel and their representations are fused before the block's output projection.

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Record: https://forck.live/items/18413-introducing-falcon-h1-arabic-pushing-the-boundaries-of-arabic-language-ai-with
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