A technical report introduces Nemotron-SEA-LION-v4.8, a family of Southeast Asian Languages in One Network models built on NVIDIA Nemotron 3, in 30B-A3B and 120B-A12B sizes with base and post-trained variants. Post-training with supervised fine-tuning and online on-policy distillation lifts SEA-HELM scores substantially across seven Southeast Asian languages. The release gives practitioners stronger regional-language models in efficient MoE configurations.
NVIDIA has made Nemotron 3.5 Lightning, an open model optimized for high-volume agentic workloads, available on Amazon SageMaker JumpStart. The model is positioned as the fastest open model in its class for always-on agents, delivering up to 4x higher throughput. Users can deploy it without configuring serving infrastructure.
NVIDIA has made Nemotron 3.5 Lightning, an open model optimized for high-volume agentic workloads, available on Amazon SageMaker JumpStart. The model is positioned as the fastest open model in its class for always-on agents, delivering up to 4x higher throughput. Users can deploy it without configuring serving infrastructure.
NVIDIA released Nemotron-3-Embed, a collection of open embedding models led by an 8B model that ranks #1 on the RTEB leaderboard, along with efficient 1B variants. The models support multilingual retrieval across 34 languages and are designed for production-scale RAG, agentic retrieval, and code retrieval. Amazon SageMaker AI now offers serverless fine-tuning for these models.
NVIDIA released Nemotron-3-Embed, a collection of open embedding models led by an 8B model that ranks #1 on the RTEB leaderboard, along with efficient 1B variants. The models support multilingual retrieval across 34 languages and are designed for production-scale RAG, agentic retrieval, and code retrieval. Amazon SageMaker AI now offers serverless fine-tuning for these models.
NVIDIA has released Nemotron 3.5 Lightning, a 30B-parameter mixture-of-experts model with 3B active parameters, designed for fast and efficient long-running agentic AI workloads. The release includes BF16 and NVFP4 quantized versions on Hugging Face, positioning it as the highest-efficiency model in its class for specialized tasks within multi-agent systems.
NVIDIA has released Nemotron 3.5 Lightning, a 30B-parameter mixture-of-experts model with 3B active parameters, designed for fast and efficient long-running agentic AI workloads. The release includes BF16 and NVFP4 quantized versions on Hugging Face, positioning it as the highest-efficiency model in its class for specialized tasks within multi-agent systems.
A llama.cpp pull request by YanissAmz adds support for NVIDIA's Nemotron-3-Puzzle-75B-A9B, a pruned-down hybrid Mamba-MoE-Attention model. The pruned variant shrinks the parent 120.7B-total-parameter model to 75.3B total / 9.3B active parameters, making it locally runnable today, though Multi-Token Prediction is not yet supported in llama.cpp.
A llama.cpp pull request by YanissAmz adds support for NVIDIA's Nemotron-3-Puzzle-75B-A9B, a pruned-down hybrid Mamba-MoE-Attention model. The pruned variant shrinks the parent 120.7B-total-parameter model to 75.3B total / 9.3B active parameters, making it locally runnable today, though Multi-Token Prediction is not yet supported in llama.cpp.
NVIDIA has released the NemotronLabs VoiceChat-11B model on Hugging Face, featuring full-duplex voice interaction. The model enables real-time, bidirectional conversation, allowing users to speak and listen simultaneously. This release advances voice AI capabilities for developers building conversational interfaces.
NVIDIA has released the NemotronLabs VoiceChat-11B model on Hugging Face, featuring full-duplex voice interaction. The model enables real-time, bidirectional conversation, allowing users to speak and listen simultaneously. This release advances voice AI capabilities for developers building conversational interfaces.