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Nvidia Nemotron 3 Nano 30B A3b Bf16Reason Fast. Scale Huge.

Try Nvidia Nemotron 3 Nano 30B A3b Bf16API Documentation

Unlock Nemotron Efficiency.

Hybrid MoE

3.5B Active Params

Activates 3.5B of 30B params per token in Nvidia Nemotron 3 Nano 30B A3b Bf16 for low-latency inference.

1M Context

Ultra-Long Sequences

Handles 1M tokens in Nvidia Nemotron 3 Nano 30B A3b Bf16 model, ideal for RAG and agents.

Top Benchmarks

Beats Qwen3 GPT-OSS

Outperforms rivals on MMLU-Pro, AIME, GPQA with Nvidia Nemotron 3 Nano 30B A3b Bf16 architecture.

Examples

See what Nvidia Nemotron 3 Nano 30B A3b Bf16 can create

Copy any prompt below and try it yourself in the playground.

Code Debug

“Analyze this Python function for bugs and suggest fixes: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2). Optimize for efficiency.”

Math Proof

“Prove that the sum of angles in a triangle is 180 degrees using Euclidean geometry axioms. Provide step-by-step reasoning.”

Document Summary

“Summarize key points from this 5000-word research paper on quantum computing advancements, focusing on error correction techniques.”

Agent Plan

“Plan a multi-step workflow for automating customer support: intake query, classify issue, retrieve knowledge base, generate response.”

For Developers

A few lines of code.
Reasoning LLM. One Call.

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

  • Serverless: scales to zero, scales to millions
  • Pay per token, no minimums
  • Python and JavaScript SDKs, plus REST API
API Documentation 
import requests


response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

FAQ

Common questions about Nvidia Nemotron 3 Nano 30B A3b Bf16

Read the docs

Nvidia Nemotron 3 Nano 30B A3b Bf16 is a 30B parameter LLM with 3.5B active params using hybrid Mamba-Transformer MoE. It supports 1M token context for reasoning tasks. Fully open weights from NVIDIA.

Access Nvidia Nemotron 3 Nano 30B A3b Bf16 API via simple HTTP POST with prompt and params. Returns reasoning trace plus final answer. Optimized for low-latency on H100 GPUs.

Features 52 layers: 23 Mamba-2, 23 MoE with 128 experts, 6 GQA. Hidden dim 2688, RMSNorm, ReLU2 activation. 3.5B active per token.

Yes, Nvidia Nemotron 3 Nano 30B A3b Bf16 beats Qwen3-30B-A3B on benchmarks like AIME (99.2% with tools) and RULER-1M. Offers 3.3x faster throughput.

Delivers high accuracy on reasoning, coding, multilingual tasks with 1M context. Cost-efficient MoE activates subset of params. Ideal for agents and RAG.

Excels in multi-step reasoning, coding, long-context retrieval. Unified for reasoning and non-reasoning via trace generation. Supports tools.

Ready to create?

Start generating with Nvidia Nemotron 3 Nano 30B A3b Bf16 on ModelsLab.

Try Nvidia Nemotron 3 Nano 30B A3b Bf16API Documentation