NVIDIA: Nemotron 3 Nano 30B A3B

Public pricingIntelligence 79/100Large memory深度思考工具调用

NVIDIA: Nemotron 3 Nano 30B A3B 是一款文本模型，适合编码、软件工程和智能体工作流。它结合了强大的编码能力、可靠的工具调用与智能体表现、262K tokens上下文和低成本定位，可在编码、软件工程和智能体工作流中提供可靠表现。它适合重视延迟、成本与吞吐的团队，能带来稳定输出、灵活部署与扩展空间。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。 它适合需要稳定回答、较长上下文、清晰结构和可扩展部署的团队。

Input

$0.05/1M

Output

$0.20/1M

Cached

$0.01/1M

Batch

$0.04/1M

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What would Nemotron 3 Nano 30B A3B cost you?

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Technical specifications

Nemotron 3 Nano 30B A3B at a glance.

Memory

262,144

tokens

Max reply

32,768

tokens

Memory tier

Large

an entire book or large codebase

Tokenizer

—

Released

Mar 2026

Training cutoff

Oct 2025

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • mmlu_pro

    78.3

  • aime_2025

    89.1

  • livecodebench

    68.3

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick Nemotron 3 Nano 30B A3B

  • Multi-step reasoning, research agents, or hard math.
  • Agentic workflows that call tools or APIs.
  • Long documents, full codebases, or extensive chat histories.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

Nemotron 3 Nano 30B A3B — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, Nemotron 3 Nano 30B A3B costs roughly $12 per month. Input is $0.05 /1M tokens and output is $0.20 /1M tokens.
Nemotron 3 Nano 30B A3B has a 262,144-token context window (large memory — an entire book or large codebase). That means you can fit about 49,152 words of input and history in a single call.
Beyond text generation, Nemotron 3 Nano 30B A3B supports deep step-by-step reasoning, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Nemotron 3 Nano 30B A3B was released in March 2026, with training data cut off around October 2025.
Models in a similar class include Nemotron 3 Super, Nemotron 3 Nano 30B A3B, Nemotron 3 Super. The "Similar models" section below this FAQ links into each.

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