NVIDIA releases Nemotron-3-Nano-Omni-30B, a 31B-parameter multimodal model with 256K context and reasoning mode
NVIDIA released Nemotron-3-Nano-Omni-30B-A3B, a multimodal large language model with 31 billion parameters that processes video, audio, images, and text with up to 256K token context. The model uses a Mamba2-Transformer hybrid Mixture of Experts architecture and supports chain-of-thought reasoning mode.
Nemotron-3-Nano-Omni-30B-A3B — Quick Specs
NVIDIA Releases Nemotron-3-Nano-Omni-30B with Multimodal Processing and Reasoning Mode
NVIDIA released Nemotron-3-Nano-Omni-30B-A3B, a 31 billion-parameter multimodal model that processes video, audio, images, and text with up to 256,000 token context length. The model is available commercially under the NVIDIA Open Model Agreement.
Architecture and Specifications
Nemotron-3-Nano-Omni uses a Mamba2-Transformer hybrid Mixture of Experts (MoE) architecture with 31B total parameters and 3B active parameters (A3B). The model combines three specialized encoders:
- Nemotron 3 Nano LLM (30B A3B) for language processing
- CRADIO v4-H vision encoder for image and video
- Parakeet speech encoder for audio
The model accepts video files up to 2 minutes at 1 FPS (1080p) or 2 FPS (720p), audio files up to 1 hour, and images in JPEG/PNG format. It supports English only.
Key Capabilities
According to NVIDIA, the model provides:
- Video and speech comprehension
- GUI automation and OCR
- Speech transcription with word-level timestamps
- JSON output format support
- Chain-of-thought reasoning mode with configurable reasoning budget (up to 16,384 tokens)
- Tool calling capabilities
Training and Development
NVIDIA states the model was improved using Qwen3-VL-30B-A3B-Instruct, Qwen3.5-122B-A10B, Qwen3.5-397B-A17B, Qwen2.5-VL-72B-Instruct, and gpt-oss-120b. Specific training methodologies and benchmark scores were not disclosed.
Deployment Requirements
The model requires vLLM 0.20.0 and runs on NVIDIA Ampere, Hopper, Blackwell, and Lovelace GPUs. Available precision formats include BF16 (~62GB), FP8, and NVFP4. NVIDIA recommends 131,072 maximum model length for single-GPU deployment with tensor-parallel-size 1.
Recommended inference parameters vary by mode:
- Thinking mode: temperature 0.6, top_p 0.95, max_tokens 20,480
- Instruct mode: temperature 0.2, top_k 1, max_tokens 1,024
The model supports deployment on edge devices including Jetson Thor and consumer hardware like RTX 5090.
Availability
Nemotron-3-Nano-Omni-30B is available on Hugging Face, Build.Nvidia.com, and NGC as of April 28, 2026. Runtime engines include vLLM, TensorRT-LLM, NeMo Megatron, llama.cpp, Ollama, and SGLang.
What This Means
NVIDIA's release targets enterprise multimodal applications that require unified processing of video, audio, and documents—use cases that previously required multiple specialized models. The 256K context window and reasoning mode position it for complex document analysis and extended video processing. The commercial license and edge deployment support (including consumer RTX 5090) differentiate it from research-focused multimodal models, though pricing and comparative benchmarks against competitors like GPT-4V or Gemini were not provided.
Related Articles
NVIDIA Releases Nemotron VoiceChat 11B, an Open Full-Duplex Speech Model with Live Tool Calling
NVIDIA has released NemotronLabs VoiceChat 11B, an 11-billion-parameter end-to-end full-duplex speech model that unifies streaming speech understanding and generation in one architecture. The model claims to be the first open full-duplex system to support live tool calling during natural conversation, with ~450ms turn-taking latency.
Mistral AI Releases Shieldstral-1.0-3B, a 3B-Parameter Policy-Adaptive Safety Classifier
Mistral AI has released Shieldstral-1.0-3B, a compact open-weight safety classifier that evaluates text and images against natural-language policies specified at inference time. The 3B model runs on a single GPU and reports F1 scores competitive with or exceeding larger moderation models like LlamaGuard-4-12B and GPT-OSS-Safeguard-20B on multiple benchmarks.
Mistral Releases Shieldstral, a 3B Open-Weights Safety Classifier That Matches Models 7x Its Size
Mistral has released Shieldstral, a 3B open-weights safety classifier that reframes content moderation as a policy-adaptive question-answering task. The model claims to match or outperform guard models up to 7x its size on text safety and multimodal benchmarks, and runs on a single 16GB GPU.
Alibaba Unveils Qwen3.8-Max, a 2.4T-Parameter Open-Weight Model for Coding and Agentic Work
Alibaba announced Qwen3.8-Max, a 2.4T-parameter flagship model targeting coding and long-horizon agentic work, with open weights promised for next week alongside Qwen3.8-27B. The model posted strong third-party benchmark results, ranking #4 in Frontend Code Arena and matching Claude Opus 4.7 on the Vals Index at roughly 2.3x lower cost.
Comments
Loading...