NVIDIA: Nemotron Nano 9B V2

Public pricingIntelligence 75/100Medium memoryRaciocínio profundoUso de ferramentas

NVIDIA: Nemotron Nano 9B V2 é um modelo texto criado para raciocínio e resolução de problemas. Ele combina raciocínio e planejamento profundos e baixa latência e inferência eficiente, um contexto de 131K tokens e um perfil baixo custo para entregar trabalho confiável em reasoning, analysis, and hard problem solving.

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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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

  • gpqa_diamond

    64

  • hellaswag

    78.9

  • ifeval

    90.3

  • math

    97.8

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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