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Nemotron 3 Super 120B A12B BF16 icon

Nemotron 3 Super 120B A12B BF16

NVIDIA
Nemotron 3 Super 120B A12B BF16 is a hybrid Mixture-of-Experts reasoning model developed by NVIDIA for large-scale agentic workflows and long-context reasoning. It features a 120B parameter architecture with ~12B active parameters, built on an 88-layer hybrid backbone combining Mamba-2 sequence layers, Transformer attention, and Latent MoE routing with 512 experts. The model incorporates Multi-Token Prediction (MTP) for faster generation and supports up to a 1M token context window, enabling efficient long-horizon reasoning, multi-agent coordination, and large-scale retrieval tasks.
TypeMoE LLM
CapabilitiesText Generation, Instruction Following, Reasoning, Mathematical Reasoning+5 more
Release Date11 March, 2026
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 -it --rm 
 --runtime=nvidia 
 --gpus all 
 --ipc=host 
 --shm-size=128g 
 -p 8000:8000 
 -v ~/.cache/huggingface:/root/.cache/huggingface 
 -e HF_TOKEN='YOUR_HF_TOKEN' 
 vllm/vllm-openai:v0.17.1 
 nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 
  --tensor-parallel-size 8 
 --max-model-len auto 
  --max-num-batched-tokens 65536 
  --gpu-memory-utilization 0.95 
  --max-num-seqs 1024 
 --max-cudagraph-capture-size 512 
 --enable-auto-tool-choice 
 --tool-call-parser qwen3_coder 
 --reasoning-parser nemotron_v3 
  --kv-cache-dtype auto 
  --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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