Abu Dhabi’s Technology Innovation Institute (TII), the applied research pillar of Abu Dhabi’s Advanced Technology Research Council (ATRC), has announced the release of Falcon H1R 7B.
This next-generation AI model takes a significant step toward making advanced AI more accessible by delivering reasoning in a compact, efficient, and openly available format.
With just 7 billion parameters, Falcon H1R 7B challenges and, in many cases, outperforms larger open-source AI models from around the world, including models from Microsoft (Phi 4 Reasoning Plus 14B), Alibaba (Qwen3 32B), and NVIDIA (Nemotron H 47B). This model release reaffirms TII’s position at the forefront of efficient AI innovation and reinforces the UAE’s growing influence in global technology leadership.
Faisal al Bannai, Adviser to the UAE President and Secretary General of the Advanced Technology Research Council, said: “Falcon H1R reflects the UAE’s commitment to building open and responsible AI that delivers real national and global value. By bringing world-class reasoning into a compact, efficient model, we are expanding access to advanced AI in a way that supports economic growth, research leadership, and long-term technological resilience.”
Falcon H1R 7B builds on the Falcon H1-7B foundation with a specialised training approach and a hybrid Transformer–Mamba architecture that improves both accuracy and speed.
“Falcon H1R 7B marks a leap forward in the reasoning capabilities of compact AI systems,” said Dr Najwa Aaraj, CEO of TII. “It achieves near-perfect scores on elite benchmarks while keeping memory and energy use exceptionally low, critical criteria for real-world deployment and sustainability.”
This approach unlocks what researchers call “latent intelligence,” enabling Falcon H1R 7B to reason more effectively and efficiently. The model sets a new Pareto frontier, a performance sweet spot where increasing speed doesn’t mean sacrificing quality.
Benchmarking
In competitive benchmarks, Falcon H1R 7B delivered standout results:
- Math: Achieved 88.1% on AIME-24, outperforming ServiceNow AI’s Apriel 1.5 (15B) (86.2%) - proving that a compact 7B model can rival or exceed much larger systems.
- Code and Agentic Tasks: Delivered 68.6% accuracy, a best-in-class performance among models under 8B, and scored higher in LCB v6, SciCode Sub and TB Hard benchmarks, with Falcon H1R scoring 34% compared to China’s DeepSeek R1-0528 Qwen 3 8B (26.9%) and even surpassing larger contenders like Qwen3-32B (33.4%).
- General Reasoning: Demonstrated strong logic and instruction-following abilities, matching or approaching the performance of larger models like Microsoft’s Phi 4 Reasoning Plus (14B), while using only half the parameters.
- Efficiency: Achieved up to 1,500 tokens/sec/GPU at batch 64, nearly doubling the speed of China’s Qwen3-8B, thanks to its hybrid Transformer–Mamba architecture - delivering faster, scalable performance without sacrificing accuracy.
“This model is the result of world-class research and engineering. It shows how scientific precision and scalable design can go hand in hand,” said Dr Hakim Hacid, Chief Researcher at TII’s Artificial Intelligence and Digital Research Centre. “We are proud to deliver a model that enables the community to build smarter, faster, and more accessible AI systems.”
Open Source and Community Driven
In line with TII’s commitment to AI transparency and collaboration, Falcon H1R 7B is released as an open-source model under the Falcon TII License. Developers, researchers, and institutions worldwide can access the model via Hugging Face, along with a full technical report detailing the training strategies and performance on key reasoning benchmarks.
This release is the latest in TII’s expanding Falcon LLM family - demonstrating the UAE’s ability to compete at the highest levels of AI and contribute meaningfully to the global scientific community.
