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NVIDIA Nemotron Nano 9B V2 (Non-reasoning)

NVIDIAOpen WeightNVIDIA Open Model License Agreement · Uso Comercial

Descripción

NVIDIA-Nemotron-Nano-9B-v2 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and tasks by first generating a reasoning trace and then concluding with a final response. The model's reasoning capabilities can be controlled via a system prompt. If the user prefers the model to provide its final answer without intermediate reasoning traces, it can be configured to do so, albeit with a slight decrease in accuracy for harder prompts that require reasoning. Conversely, allowing the model to generate reasoning traces first generally results in higher-quality final solutions to queries and tasks.

Fecha de lanzamiento
2025-08-18
Parámetros
8.9B
Longitud del contexto
131K
Modalidades
text

Radar de capacidades

27
general
70
coding
61
reasoning
40
science
64
agents
0
multimodal

Rankings

Dominio#PosiciónPuntuaciónFuente
Ranking de codificación389
35.0
AA
Ranking general498
28.0
AA
Ciencia465
30.0
AA

Puntuaciones de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Chat

IFEvalGoogle Research (2023)90.3%Aut.

General

BFCL_v3_MultiTurn66.9%Aut.

Math

MATH-50097.8%Aut.
AIME 202572.1%Aut.

Reasoning

LiveCodeBench71.1%Aut.
GPQANYU + Cohere + Anthropic (2023)64.0%Aut.

Índices de evaluación AA

(Artificial Analysis)
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
73.9
Livecodebench(UC Berkeley + MIT + Cornell (2024))
70.1
Aime 25(MAA (Mathematical Association of America))
62.3
Math Index(Artificial Analysis)
62.3
Gpqa(NYU + Cohere + Anthropic (2023))
55.7
Ifbench(Google Research (2023))
27.1
Lcr(Artificial Analysis)
24.0
Tau2(Sierra + U Toronto + Vector Institute (2025))
23.4
Intelligence Index(Artificial Analysis)
6.8
Hle(Center for AI Safety + Scale AI (2025))
4.6
Terminalbench Hard(Stanford × Laude Institute (2026))
0.8

Puntuaciones por categoría LLM Stats

(LLM Stats (zeroeval))
Chat
90
Instruction Following
90
Structured Output
90
Math
80
Reasoning
80
General
80
Code
70
Physics
60
Biology
60
Chemistry
60

Precios

Precio de entrada$0.05 / 1M tokens
Precio de salida$0.195 / 1M tokens
Precio mixto (3:1)$0.086 / 1M tokens

Velocidad

Tokens/seg159.4
Retraso del primer token1.16s
Tiempo hasta la respuesta1.16s

Ranking de Precios por Proveedor

Ranking de Precios por Proveedor

1 proveedores

ProveedorEntradaSalida
1NVIDIAPRINCIPAL
$0.05
$0.195

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas