Introducing the Nemotron-H Reasoning Model Family: Throughput Gains Without Compromise – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-07-11T15:00:00Z http://www.open-lab.net/blog/feed/ Adi Renduchintala <![CDATA[Introducing the Nemotron-H Reasoning Model Family: Throughput Gains Without Compromise]]> http://www.open-lab.net/blog/?p=101373 2025-06-12T18:48:43Z 2025-06-06T17:00:00Z As large language models increasingly take on reasoning-intensive tasks in areas like math and science, their output lengths are getting significantly...]]> As large language models increasingly take on reasoning-intensive tasks in areas like math and science, their output lengths are getting significantly...

As large language models increasingly take on reasoning-intensive tasks in areas like math and science, their output lengths are getting significantly longer��sometimes spanning tens of thousands of tokens. This shift makes efficient throughput a critical bottleneck, especially when deploying models in real-world, latency-sensitive environments. To address these challenges and enable the��

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