Nemotron 3.5 Lightning
A Mixture-of-Experts (MoE) large language model released by NVIDIA, with approximately 30 billion total parameters of which only about 3 billion are activated per token. This architecture maintains substantial knowledge capacity while achieving high inference efficiency.
Core Facts
Timeline (last 90 days)
The video mentioned that the technical details of Nemotron 3.5 Lightning will also be included in the technical report, showing that this generation of the product line has more than one model.
Nemotron 3.5 Lightning uses a hybrid structure that interleaves Mamba-2 with MoE layers, paired with a small number of attention layers.
Nemotron 3.5 Lightning supports a 1 million token context window, tool calling, and structured outputs.
Nemotron 3.5 Lightning is positioned for long-running agents, sub-agent collaboration, chatbots, and RAG systems, rather than one-off question answering.
The official documentation notes that the provider may retain prompts for model improvement.
For teams handling sensitive data, private code, or high compliance requirements, using free models that retain prompts requires evaluating data anonymization or switching to other deployment methods.
When running the NVIDIA Nemotron 3.5 Lightning model, the Mac mini generates approximately 38 tokens per second, while the Mac Studio generates approximately 124 tokens per second.
The article recommends that beginners start with Nemotron 3.5 Lightning paired with LoRA, because this combination can lower the entry barrier to a range affordable with a single mid-to-low-end GPU.
NVIDIA的Nemotron 3.5 Lightning模型经过2-bit量化后仍能持续运行工具调用长达10分钟以上
This observation of tool-calling performance comes from a single community source and represents a personal usage experience, with no large-scale third-party benchmark tests or reproduction reports to support it.
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All Facts (11)
Nemotron 3.5 Lightning is a 30B-scale Mixture of Experts (MoE) model that activates only approximately 3B parameters per inference.
75%UnverifiedThe video mentioned that the technical details of Nemotron 3.5 Lightning will also be included in the technical report, showing that this generation of the product line has more than one model.
50%UnverifiedNemotron 3.5 Lightning uses a hybrid structure that interleaves Mamba-2 with MoE layers, paired with a small number of attention layers.
50%UnverifiedNemotron 3.5 Lightning is positioned for long-running agents, sub-agent collaboration, chatbots, and RAG systems, rather than one-off question answering.
50%UnverifiedThe official documentation notes that the provider may retain prompts for model improvement.
50%UnverifiedFor teams handling sensitive data, private code, or high compliance requirements, using free models that retain prompts requires evaluating data anonymization or switching to other deployment methods.
50%UnverifiedNemotron 3.5 Lightning supports a 1 million token context window, tool calling, and structured outputs.
50%UnverifiedWhen running the NVIDIA Nemotron 3.5 Lightning model, the Mac mini generates approximately 38 tokens per second, while the Mac Studio generates approximately 124 tokens per second.
50%UnverifiedThe article recommends that beginners start with Nemotron 3.5 Lightning paired with LoRA, because this combination can lower the entry barrier to a range affordable with a single mid-to-low-end GPU.
50%UnverifiedNVIDIA的Nemotron 3.5 Lightning模型经过2-bit量化后仍能持续运行工具调用长达10分钟以上
50%UnverifiedNVIDIA推出了名为Nemotron 3.5 Lightning的开源模型
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