Nemotron 3 Nano 30B A3B (free)
Nemotron 3 Nano 30B A3B is NVIDIA’s open-weight, 30B-parameter hybrid Mixture-of-Experts Mamba-Transformer language model optimized for efficient reasoning and long-context workloads.
What is Nemotron 3 Nano 30B A3B (free)?
Nemotron 3 Nano 30B A3B is a 30-billion-parameter open-weight large language model from NVIDIA based on a hybrid Mixture-of-Experts Mamba-Transformer architecture tailored for efficient reasoning. It is designed for agentic and tool-using workflows such as code generation, math and science problem solving, and long-context analysis of documents and conversations. It is also used as the language backbone for multimodal systems like Nemotron 3 Nano Omni, supporting downstream tasks including computer-use agents and enterprise assistants. The model belongs to NVIDIA’s Nemotron 3 family (Nano, Super, Ultra), succeeding earlier Nemotron generations with a focus on open, efficient reasoning at 30B scale.
Providers
Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Exacto (highest tool-calling accuracy).
| Provider | Input | Output | Cache read /M | Latency | Throughput | Uptime |
|---|---|---|---|---|---|---|
| NVIDIA | $0.00 | $0.00 | — | ~200ms | ~40 tps | 99.9% |
| AWS Bedrock (Nemotron-equivalent 30B) | ~$0.60 | ~$0.60 | — | ~220ms | ~35 tps | 99.9% |
| Google Cloud (Nemotron-equivalent 30B) | ~$0.55 | ~$0.55 | — | ~210ms | ~38 tps | 99.9% |
| Azure AI Studio (Nemotron-equivalent 30B) | ~$0.65 | ~$0.65 | — | ~230ms | ~30 tps | 99.9% |
Try this model
Test Nemotron 3 Nano 30B A3B (free) right here — free to start.
Suggestions for your first prompt
Code snippet
Call the model through the OpenAI-compatible API.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://inference.example.com/v1"
)
response = client.chat.completions.create(
model="nvidia/nemotron-3-nano-30b-a3b-free",
messages=[
{
"role": "user",
"content": "Describe this image in one sentence."
}
],
)
print(response.to_json())
{
"model": "nvidia/nemotron-3-nano-30b-a3b-free",
"messages": [
{
"role": "user",
"content": "Describe this image in one sentence."
}
]
}
5 Core Capabilities
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Conversational Chat
Handles multi-turn natural language conversations, answering questions, following instructions, and maintaining context across user interactions.
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Code Assistance
Generates and explains code snippets, helps with debugging, and provides programming guidance for common languages and libraries.
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Language Translation
Translates between major natural languages, preserving meaning and tone while producing fluent, grammatically correct output.
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Text Analysis
Summarizes, rewrites, and classifies text, extracting key information and improving clarity while retaining original intent.
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Vision Understanding
Interprets image content, identifying objects, scenes, and relationships to support multimodal reasoning and description tasks.
6 Most Valuable Use Cases
- On-device Text Generation
- Code Autocompletion
- Chat-based Assistants
- Language Translation Support
- Edge AI Applications
- GPU Inference Optimization
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
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Intelligent Model Routing
Automatically route each request to the optimal model across providers based on latency, cost, and capability—without changing your integration or redeploying code.
One endpoint, many models -
Cost-Aware Orchestration
Control spend with price-based routing, hard budget guards, and granular usage controls while still accessing frontier models when they deliver meaningful value.
Lower spend, same quality -
Resilient Fallback Flows
Define automatic failover chains so requests transparently retry on backup models or providers, reducing downtime and flaky responses without application-level logic.
Always-on AI reliability -
Full-Stack Observability
Trace every call across providers with logs, metrics, and latency breakdowns so you can debug prompts, tune routing, and catch regressions in production.
See every token, everywhere -
Task-Native Abstractions
Use high-level task APIs for chat, generation, extraction, tools, and RAG so you can swap models without rewriting business logic or prompt scaffolding.
Code to tasks, not models -
High-Throughput Batch Jobs
Run large-scale batch inference with concurrency controls, retries, and progress tracking—ideal for backfills, fine-tuning prep, and bulk content generation.
Ship massive workloads fast
When to Use — When NOT to Use
Use it if...
- You need a fully local, free LLM for experimentation without ongoing API costs.
- Your use case involves basic chatbots, assistants, or agents with moderate reasoning needs.
- You need on-device inference on NVIDIA GPUs where small footprint and speed matter.
- Your use case involves fine-tuning or LoRA training on a 30B-parameter open model.
- You need to prototype LLM features in an application before committing to larger models.
- Your use case involves educational or hobby projects that must avoid paid proprietary APIs.
Avoid if...
- You need cutting-edge reasoning, planning, or coding performance comparable to frontier proprietary models.
- Your workload requires extremely long context handling, such as book-length documents or transcripts.
- You need state-of-the-art multilingual understanding and generation across many low-resource languages.
- Your workload requires highly reliable safety, hallucination resistance, and enterprise-grade alignment guarantees.
- You need ultra-low-latency, high-concurrency serving for millions of users without GPU scaling complexity.
- Your workload requires specialized capabilities like high-quality vision, speech, or tool use beyond text.
Frequently Asked Questions
-
What is Nemotron 3 Nano 30B A3B (free)?
Nemotron 3 Nano 30B A3B (free) is a 30-billion-parameter NVIDIA language model optimized for efficient text generation and reasoning via LLM.API.
-
What is Nemotron 3 Nano 30B A3B (free) best suited for?
It is best suited for fast, low-cost code completion, chatbots, and general-purpose text generation where latency and efficiency matter.
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How much does it cost to use Nemotron 3 Nano 30B A3B (free) on LLM.API?
Nemotron 3 Nano 30B A3B (free) is available at zero per-token cost on LLM.API, subject to fair-use and rate limits.
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What is the context window of Nemotron 3 Nano 30B A3B (free)?
Nemotron 3 Nano 30B A3B (free) supports a 4,096-token context window for combined input and output on LLM.API.
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Which modalities does Nemotron 3 Nano 30B A3B (free) support?
Nemotron 3 Nano 30B A3B (free) is a text-only model, supporting text prompts and text completions but not images, audio, or video.
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How do I call Nemotron 3 Nano 30B A3B (free) through the LLM.API?
You select the NVIDIA provider and specify the model name "nemotron-3-nano-30b-a3b-free" in your LLM.API completion or chat request.
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What latency and speed should I expect from Nemotron 3 Nano 30B A3B (free)?
As a nano-optimized 30B model, it typically returns first tokens within a few hundred milliseconds under normal LLM.API load.
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How does Nemotron 3 Nano 30B A3B (free) compare to similar 30B-class models?
It generally offers competitive quality to other 30B open models while emphasizing inference efficiency and lower cost on NVIDIA-optimized hardware.
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What are the main limitations of Nemotron 3 Nano 30B A3B (free)?
It can hallucinate facts, lacks real-time knowledge, and is less suitable for very long documents due to its 4K context window.
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Can I use Nemotron 3 Nano 30B A3B (free) for commercial applications?
Yes, commercial use is allowed through LLM.API, subject to NVIDIA’s model license and LLM.API terms of service.
COMPARE
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-
MiniMax M2
MiniMax M2 is an open‑weight Mixture‑of‑Experts large language model from MiniMax, designed to deliver high coding and agentic workflow performance with low latency and cost. It uses 230B total parameters with only about 10B active per token to balance strong reasoning with efficient deployment.
-
Nano Banana 2 (Gemini 3.1 Flash Image Preview)
Nano Banana 2 (Gemini 3.1 Flash Image Preview) is Google DeepMind’s image generation and editing model built on the Gemini 3.1 Flash architecture, optimized for fast, cost‑efficient, high‑quality visuals. It balances strong multimodal understanding with 4K-capable output and low latency for both text-to-image and image-edit tasks.
-
GLM 4.6
GLM 4.6 is Z.ai’s flagship mixture-of-experts large language model optimized for coding, reasoning, and agentic workflows. It is notable for its strong performance on code benchmarks and its very long ~200K token context window for complex tasks.
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