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Nemotron 3 Nano 30B A3B BF16 icon

Nemotron 3 Nano 30B A3B BF16

NVIDIA
Nemotron-3-Nano-30B-A3B-BF16 is a hybrid Mixture-of-Experts (MoE) large language model built for both reasoning-intensive and general-purpose AI workloads. The model contains 30B total parameters with 3.5B active parameters, activating 6 experts per token across 128 routed experts and 1 shared expert. Architecturally, it features 52 layers combining MoE, Mamba-2 state space layers, and grouped query attention, with 32 attention heads and a 2,688 hidden size. Supporting up to a 1M token context window, it is optimized for configurable reasoning, agentic workflows, and commercial AI deployments.
TypeMoE LLM
CapabilitiesText Generation, Instruction Following, Reasoning, Mathematical Reasoning+5 more
Links
Paper|Blog|HF Model Card
Licensenvidia-open-model-license

Inference Instructions

Deploy and run this model on NVIDIA B200 GPUs using the command below. Copy the command to get started with inference.

CONSOLE
docker run --gpus all 
 --shm-size 128g 
 -p 8000:8000 
 -v ~/.cache/huggingface:/root/.cache/huggingface 
 -e HF_TOKEN='YOUR_HF_TOKEN' 
 --ipc=host 
 lmsysorg/sglang:v0.5.8-cu130 
 python3 -m sglang.launch_server 
 --model-path nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 
 --host 0.0.0.0 
 --port 8000 
 --max-prefill-tokens 65536 
 --max-running-requests 1024 
 --tp 8 
 --mem-fraction-static 0.95 
 --tool-call-parser qwen3_coder 
 --reasoning-parser deepseek-r1 
 --trust-remote-code

Model Benchmarks

Each model was tested with a fixed input size and total token volume while increasing concurrency to measure serving performance under load.

ITL vs Concurrency

Time to First Token

Throughput Scaling

Total Tokens/sec vs Avg TTFT

Vultr Cloud GPU

NVIDIA HGX B200

Deploy NVIDIA B200 on Vultr Cloud GPU

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