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Available now on ModelsLab · Language Model

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

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
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

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