Nemotron 3 Nano 30B A3B: Complete Specifications, Pricing, API Access & Use Cases (2026)

What Is Nemotron 3 Nano 30B A3B?

Nemotron 3 Nano 30B A3B is NVIDIA’s text-only hybrid Mamba-Transformer Mixture-of-Experts large language model, released on December 15, 2025. It features configurable reasoning behavior, 128K-token hosted API input and output limits, and up to 1M-token context in supported self-hosted configurations.

In the user-provided Gate.AI model card, the free-model pricing is shown as US$0.00 per 1M input tokens and US$0.00 per 1M output tokens as of June 2026. NVIDIA identifies the model developer as NVIDIA Corporation, lists pre-training data freshness through June 25, 2025 and post-training data freshness through November 28, 2025, and describes the model as a unified reasoning and non-reasoning LLM.

NVIDIA describes Nemotron as a family of open models with open weights, training data, and recipes for building specialized AI agents. Nemotron 3 Nano 30B A3B is the compact member relevant to developers evaluating reasoning, code, RAG, chat, and agentic workloads where self-hosting or gateway-based API access matters.

Teams researching this model often compare it with other reasoning or open-weight systems such as DeepSeek-R1, DeepSeek-V3, and Qwen2.5 72B Instruct, especially when balancing cost, deployment control, context length, and tool-use behavior.

What Are Nemotron 3 Nano 30B A3B’s Key Specifications and Pricing?

Data reference date: June 2026.

What Can Nemotron 3 Nano 30B A3B Do That Makes It Useful in Production?

Nemotron 3 Nano 30B A3B is relevant for AI agent prototypes because NVIDIA describes it as a general-purpose reasoning and chat model for developers building AI agent systems, chatbots, RAG systems, and instruction-following applications. This makes it suitable for evaluation in workflow automation, tool-assisted assistants, and internal developer tools, provided teams test tool reliability and safety behavior on their own tasks.

The model is useful for long-context experimentation when teams can control deployment. NVIDIA’s hosted model-card fields list 128K maximum input and 128K maximum output, while NVIDIA also states the model can support up to 1M context in self-hosted configurations with higher VRAM requirements. That distinction is important for document review, repository analysis, and RAG pipelines.

For coding and technical question answering, NVIDIA lists coding languages and developer applications among intended uses. The model’s post-training includes synthetic code, math, science, tool calling, instruction following, structured outputs, and general knowledge data, but production teams should still benchmark it against their own codebase, latency budget, and failure tolerance.

For gateway-based testing, Gate.AI documentation verifies an OpenAI-compatible base URL, bearer-token authentication, pay-as-you-go pricing format, /chat/completions, and /models. Gate.AI’s public homepage also identifies Nemotron among model families available through its 200+ model coverage, while the exact free model ID and US$0.00 pricing come from the user-provided Gate.AI model-card screenshot.

What Are Nemotron 3 Nano 30B A3B’s Supported Modalities?

Where Does Nemotron 3 Nano 30B A3B Fall Short?

The main specification caveat is deployment-dependent context length. The NVIDIA model card lists 128K maximum input and 128K maximum output, while the same documentation also states that self-hosted configurations can increase context up to 1M. Teams should not assume every API route supports 1M tokens.

The model is text-only in the cited NVIDIA model card. It should not be treated as a multimodal model, and image, audio, or video use cases should be routed to a model explicitly documented for those modalities.

The official supported-language list includes English, Spanish, French, German, Japanese, and Italian. NVIDIA also describes broader training data, but production quality in languages outside the supported list should be evaluated separately.

This is a general AI limitation and is not model-specific unless stated by the provider: the model may hallucinate, misread instructions, produce unsafe outputs, mishandle tool calls, or fail on high-stakes legal, medical, financial, cybersecurity, or compliance tasks. Expert review and application-level safeguards are required for high-risk use.

What Is Nemotron 3 Nano 30B A3B Best Used For?

Teams comparing open or gateway-accessible models may also evaluate Mistral Small 4 for lighter production routing or Llama 3.1 70B for an established open-model baseline.

How Does Nemotron 3 Nano 30B A3B Compare to Qwen3-30B-A3B-Thinking-2507 and GPT-OSS-20B?

How Do I Access Nemotron 3 Nano 30B A3B Through Gate.AI?

Gate.AI access for Nemotron 3 Nano 30B A3B is verified by the user-provided Gate.AI model-card screenshot, which lists the model ID nvidia/nemotron-3-nano-30b-a3b:free.

Gate.AI documentation verifies the OpenAI-compatible base URL https://api.gate.ai/openai/v1, bearer-token authentication, POST /chat/completions, GET /models, pay-as-you-go pricing format, and streaming support for chat completions.

Python Example

from openai import OpenAI
import os
client = OpenAI(
    api_key=os.environ["GATEAI_API_KEY"],
    base_url="https://api.gate.ai/openai/v1",
)
response = client.chat.completions.create(
    model="nvidia/nemotron-3-nano-30b-a3b:free",
    messages=[
        {
            "role": "user",
            "content": "Summarize Nemotron 3 Nano 30B A3B in three bullet points."
        }
    ],
)
print(response.choices[0].message.content)

curl Example

curl https://api.gate.ai/openai/v1/chat/completions \
  -H "Authorization: Bearer $GATEAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nvidia/nemotron-3-nano-30b-a3b:free",
    "messages": [
      {
        "role": "user",
        "content": "Explain what Nemotron 3 Nano 30B A3B is used for."
      }
    ]
  }'

Gate.AI pricing documentation describes a free tier for free models, pay-as-you-go billing for 200+ models, API key management, smart routing, prompt caching where supported, usage insights, and organization permissions. Production teams should still check their dashboard for model-specific quotas, route availability, and free-model daily limits.

FAQs

What is Nemotron 3 Nano 30B A3B’s context window?

NVIDIA lists 128K maximum input and 128K maximum output in the hosted model-card fields, while also stating that supported self-hosted configurations can increase context up to 1M tokens.

How much does Nemotron 3 Nano 30B A3B cost on Gate.AI?

The user-provided Gate.AI model card lists nvidia/nemotron-3-nano-30b-a3b:free at US$0.00 per 1M input tokens and US$0.00 per 1M output tokens as of June 2026.

How can developers access Nemotron 3 Nano 30B A3B?

Developers can use the Gate.AI OpenAI-compatible chat API with the verified Gate.AI model ID. NVIDIA also documents Build / NIM and self-hosted options through Hugging Face, vLLM, TRT-LLM, and SGLang.

What is Nemotron 3 Nano 30B A3B useful for?

It may fit AI agents, coding assistance, RAG, document analysis, instruction following, and open-weight experimentation. Teams should test latency, hallucination behavior, safety, and tool-call reliability before production use.