A Blog post by NVIDIA on Hugging Face

NVIDIA today announced the open Llama Nemotron family of models with reasoning capabilities, designed to provide developers and enterprises a business-ready foundation for creating advanced AI agents that can work independently or as connected teams to solve complex tasks.

NVIDIA just made a big move in open-source AI. Last week, the company released OpenReasoning-Nemotron. It’s a new family of compact but powerful models designed for complex reasoning across math, code, and science. You can grab them right now on Hugging Face. These models don’t just work well. They set new performance records in their […]

NVIDIA AI has introduced OpenReasoning-Nemotron, a family of large language models (LLMs) designed to excel in complex reasoning tasks across mathematics, science, and code. This model suite—comprising 1.5B, 7B, 14B, and 32B parameter versions—has been distilled from the 671B DeepSeek R1 0528 model, capturing its high-level reasoning capabilities in significantly smaller and more efficient models. The release positions NVIDIA as a leading contributor to the open-source LLM ecosystem, delivering models that push state-of-the-art (SOTA) performance while remaining commercially permissive and widely accessible via Hugging Face.

Today, NVIDIA unveiled OpenReasoning-Nemotron, a quartet of distilled reasoning models with 1.5B, 7B, 14B, and 32B parameters, all derived from the 671B-parameter DeepSeek R1 0528. By compressing that massive teacher into four leaner Qwen‑2.5-based students, NVIDIA is making advanced reasoning experiments accessible even on standard gaming rigs, without the need to worry about hefty GPU bills and cloud usage. The key is not some elaborate trick but raw data. Using the NeMo Skills pipeline, NVIDIA generated five million math, science, and code solutions, and then fine-tuned each one purely with supervised learning. Already, the 32B model hits an 89.2 on AIME24 and 73.8 on the HMMT February contest, while even the 1.5B variant manages a solid 55.5 and 31.5. NVIDIA envisions these models serving as a powerful research toolkit. All four checkpoints will be available for download on Hugging Face, providing a strong baseline for exploring reinforcement-learning-driven reasoning or customizing the models for specific tasks. With GenSelect mode (which takes multiple passes for each question), you can spawn multiple parallel generations and pick the best answer, pushing the 32B model to outstanding performance that rivals or even exceeds OpenAI's o3‑high performance on several math and coding benchmarks. Since NVIDIA trained these models with supervised fine-tuning only, without reinforcement learning, the community has clean, state-of-the-art starting points for future RL experiments. For gamers and at-home enthusiasts, we get a model that can be very close to the state-of-the-art, entirely locally, if you have a more powerful gaming GPU.

🔍 Introduction: A Bold Leap in Reasoning-Focused AI In the fast-evolving world of large language models (LLMs), precision and reasoning are the new frontiers. The latest release—OpenReasoning-Nemotron—marks a significant milestone in the pursuit of highly capable, domain-specific reasoning AIs. Distilled from the powerful DeepSeek R1 0528 671B, these new models (1.5B, 7B, 14B, and 32B) aim to redefine what's possible in math, science, and code problem-solving.

NVIDIA AI has launched OpenReasoning-Nemotron, a household of enormous language fashions (LLMs) designed to excel in advanced reasoning duties throughout arithmetic, science, and code. This mannequin suite—comprising 1.5B, 7B, 14B, and 32B parameter variations—has been distilled from the 671B DeepSeek R1 0528 mannequin, capturing its high-level reasoning capabilities in considerably smaller and extra environment friendly fashions. The discharge positions NVIDIA as a number one contributor to the open-source LLM ecosystem, delivering fashions that push state-of-the-art (SOTA) efficiency whereas remaining commercially permissive and extensively accessible by way of Hugging Face.

英伟达推出OpenReasoning-Nemotron推理模型套件，包含四个基于Qwen-2.5微调的模型，参数规模从1.5B到32B不等。这些模型通过蒸馏技术降低了部署门槛，使得在标准游戏电脑上也能进行高级推理实验。32B模型在多项数学竞赛中表现优异，甚至超越OpenAI o3-high。 #AI #英伟达

Ekran kartı ve yapay zekâ devi Nvidia, OpenReasoning-Nemotron adlı yeni yapay zekâ modellerini kullanıma sundu. Buradan elde edilebilen 1,5B, 7B, 14B ve 32B parametreye sahip OpenReasoning-Nemotron serisi yapay zekâ modelleri, 671 milyar parametreli DeepSeek R1 0528 kullanılarak türetilmiş. Güçlü akıl yürütme yeteneklerine sahip bu modelleri, bulut servislerine ya da pahalı donanımlara ihtiyaç duymadan kişisel bilgisayarlarda bile rahatlıkla çalıştırılabilmeleri için hazırlayan Nvidia, yeni modelleri yalnızca denetimli öğrenme (supervised learning) ile eğitmiş; yani takviye öğrenme (reinforcement learning) gibi karmaşık yöntemler kullanılmamış. Şirket, 32B parametreli versiyonun özellikle GenSelect moduyla birlikte çok yüksek performans gösterebildiğini belirtiyor. Her soru için birden fazla cevap üretilip en iyisinin seçilmesini temel alan bu mod, 32B parametreli modelin bazı testlerde OpenAI’ın o3-high modelini geride bırakmasını sağlıyor. Şirketin resmi verilerine göre 32B model AIME24’te 89,2 ve HMMT Şubat yarışmasında 73,8 puan alırken, en alttaki 1,5B parametreli model dahi sırasıyla 55,5 ve 31,5 gibi iyi sonuçlar elde ediyor. Nvidia, geçtiğimiz hafta […] Nvidia, OpenReasoning-Nemotron adlı yeni yapay zeka modellerini kullanıma sundu yazısı ilk olarak Teknoloji haberleri - LOG üzerinde yayınlandı.

YouTube video by MutedGiant4126

NVIDIA wprowadza OpenReasoning-Nemotron — rodzinę otwartych modeli językowych (LLM) zoptymalizowanych pod kątem złożonych zadań rozumowania. Modele te, destylowane z potężnego DeepSeek R1, mają zapewnić wysoką wydajność w matematyce, naukach ścisłych i programowaniu, zachowując jednocześnie mniejsze rozmiary i szeroką dostępność.