NVIDIA: Nemotron Nano 9B V2

Public pricingIntelligence 75/100Medium memory深い思考ツール利用

NVIDIA: Nemotron Nano 9B V2 は テキスト モデルで、推論と問題解決 に向いています。深い推論と計画、低遅延で効率的な推論、131K tokensのコンテキスト、低コストの特性を組み合わせ、reasoning, analysis, and hard problem solving で安定した動作を支えます。遅延・コスト・スループット が重要な場面に合っており、安定した出力、柔軟な導入、拡張性を求めるチームに実用的です。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。 安定した応答、長い文脈処理、そして試作から本番まで広く使える柔軟さが必要な場面で役立ちます。

Input

$0.04/1M

Output

$0.16/1M

Cached

$0.00/1M

Batch

$0.02/1M

Calculate your Nemotron Nano 9B V2 bill.

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What would Nemotron Nano 9B V2 cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

Nemotron Nano 9B V2 at a glance.

Memory

131,072

tokens

Max reply

32,768

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

—

Released

Aug 2025

Training cutoff

Apr 2025

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • aime_2025

    72.1

  • math

    97.8

  • gpqa_diamond

    64

  • ifeval

    90.3

  • hellaswag

    78.9

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 Nano 9B V2

  • Multi-step reasoning, research agents, or hard math.
  • Agentic workflows that call tools or APIs.
  • 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 Nano 9B V2 — 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 Nano 9B V2 costs roughly $9 per month. Input is $0.04 /1M tokens and output is $0.16 /1M tokens.
Nemotron Nano 9B V2 has a 131,072-token context window (medium memory — a long report or a codebase file). That means you can fit about 24,576 words of input and history in a single call.
Beyond text generation, Nemotron Nano 9B V2 supports deep step-by-step reasoning, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
Nemotron Nano 9B V2 was released in August 2025, with training data cut off around April 2025.
Models in a similar class include Nemotron 3 Nano 30B A3B, Nemotron 3 Nano 30B A3B, Nemotron 3 Super. The "Similar models" section below this FAQ links into each.

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