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Mini toolsNemotron models
Browse all models from this model family.
ID
Model
Company
Type
Primary task
Open source
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By NVIDIANemotron-Labs-Audex-30B-A3B is a unified audio-text large language model from NVIDIA built on a 30B parameter Mixture-of-Experts backbone with 3B active parameters. It extends a strong text-only reasoning model with an audio encoder and discrete audio token vocabulary, enabling audio understanding, speech recognition, speech translation, text-to-speech, audio generation, and speech-to-speech interaction while preserving the backbone's reasoning, knowledge, and long-context abilities.NewMultimodalReleased 1mo ago
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By NVIDIANVIDIA Nemotron-3-Ultra-550B-A55B-NVFP4 is NVIDIA’s open 550B total, 55B active frontier reasoning LLM for agentic workflows, long-context analysis, tool use, code, math, and science.NewTextReleased 1mo ago
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By NVIDIANemotron-Labs-Diffusion-14B is NVIDIA’s open 14B text-generation language model that supports autoregressive decoding, diffusion-style parallel decoding, and self-speculative decoding.NewTextReleased 1mo ago
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By NVIDIANemotron 3 Nano Omni is NVIDIA’s open multimodal reasoning model for agentic systems. It unifies text, image, video, and audio in a single efficient 30B-A3B hybrid MoE model, built to replace fragmented vision-language-audio stacks with one shared perception-and-context model for multimodal agents.NewMultimodalReleased 2mo ago
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By NVIDIANemotron-Cascade 2 is an open 30B Mixture-of-Experts model (3B activated) trained with Cascade RL and multi-domain on-policy distillation for strong reasoning and agentic capabilitieTextReleased 4mo ago
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By NVIDIANemotron 3.5 ASR is a 600M parameter multilingual streaming automatic speech recognition model supporting 40 language locales in a single checkpoint. Built on a cache-aware FastConformer-RNNT architecture, it maintains encoder context across audio chunks for accurate real-time transcription with native punctuation and capitalization output.AudioReleased 4mo ago
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By NVIDIANemotron 3 Super is NVIDIA’s open Mixture-of-Experts hybrid Mamba-Transformer model designed for high-throughput agentic workloads and long-context reasoning.TextReleased 4mo ago
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By NVIDIANemotron-3-Nano-30B-A3B is NVIDIA’s 30B-class LLM trained from scratch as a unified model for both reasoning and standard chat tasks. It can be configured to produce a reasoning trace before the final answer, letting developers switch reasoning behavior through the chat template.TextReleased 6mo ago
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By NVIDIATextReleased 7mo ago
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TextReleased 7mo ago
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By NVIDIALlama-3.3-Nemotron-Super-49B-v1.5 is NVIDIA’s upgraded 49B reasoning model derived from Meta Llama-3.3-70B-Instruct. It is post-trained for reasoning, chat preference alignment, and agentic tasks such as RAG and tool use.TextReleased 9mo ago
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By NVIDIANemotron-4 is NVIDIA’s open-weight LLM family (from compact to 340B) built for high-quality reasoning, coding, and synthetic data generation. It supports tool/function calling, JSON outputs, and long-context variants, and is production-ready via NVIDIA NIM/TensorRT-LLM for fast, scalable deployment.TextReleased 9mo ago
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TextReleased 10mo ago
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By NVIDIANemotron-Nano 2 is NVIDIA’s ultra-compact LLM tuned for on-device and edge deployment. It delivers fast instruction following, coding help, and reasoning with low memory use, supports tool/function calling and structured (JSON) outputs, and runs efficiently on Jetson, RTX laptops/desktops, and server GPUs.TextReleased 10mo ago
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By NVIDIALlama 3.1 Nemotron Ultra is an NVIDIA-optimized deployment of Meta’s Llama 3.1, packaged for high-throughput production. It delivers strong reasoning and coding, long-context support (≈128K), tool/function calling, and JSON mode—served as a fast, scalable NIM for apps and agents.TextReleased 1y ago
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By NVIDIACosmos Nemotron VLM is NVIDIA’s multimodal model that fuses Cosmos world-model perception with Nemotron language reasoning. It understands images and video alongside text, performs step-by-step visual reasoning, and supports tool/function calling and JSON outputs—optimized for fast, scalable deployment via TensorRT-LLM and NIM.TextReleased 1y ago
