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OpenAI: GPT-4.1 Nano (batch)

openai/gpt-4.1-nano:batch

Comparar

For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million token context window, and scores 80.1% on MMLU, 50.3% on GPQA, and 9.8% on Aider polyglot coding – even higher than GPT‑4o mini. It’s ideal for tasks like classification or autocompletion.

Modalidades
Precio de entrada / salida
0,05 US$ / 0,20 US$por 1M
Contexto
1,0M
Publicado
14 abr 2025
Fecha de corte del conocimiento
jun 2024
Comparar
ProveedoresPreciosRendimientoTiempo de actividadPruebas de rendimientoAplicacionesActividadDocumentaciónPreguntas frecuentesExplorar

Proveedores

Distintas empresas alojan el mismo modelo. OpenRouter dirige su solicitud a una de ellas según el modo de enrutamiento que elija: Equilibrado (precio + velocidad), Nitro (el más rápido) o Floor (el más barato).

Precios

El precio medio que los clientes pagan realmente por este modelo, junto a los precios que publican los proveedores. El uso de caché y los descuentos hacen que el precio realmente pagado a menudo sea muy inferior al publicado.

Rendimiento

La velocidad de generación indica lo rápido que escribe el modelo (tokens por segundo: cuanto mayor, mejor). La latencia es el tiempo total de ida y vuelta (cuanto menor, mejor). TTFT es el tiempo hasta el primer token: cuánto tarda en aparecer algo en pantalla (cuanto menor, mejor).

Tiempo de actividad

El tiempo de actividad es el porcentaje de los últimos 3 días en que al menos un proveedor respondía a las solicitudes. La disponibilidad es el porcentaje de tiempo en que la inferencia se sirvió correctamente. OpenRouter supervisa continuamente y utiliza el siguiente mejor proveedor cuando uno devuelve un error.

Pruebas de rendimiento

Puntuaciones en evaluaciones estandarizadas y respuestas de este modelo a instrucciones compartidas de las pruebas de referencia. Los porcentajes más altos son mejores, y cada posición indica dónde se sitúa este modelo entre los modelos evaluados en esa fuente.

Resumen de puntuaciones en pruebas de rendimiento de OpenAI: GPT-4.1 Nano (batch) (Artificial Analysis, Design Arena y Vals AI)
FuentePrueba de rendimientoPuntuación
Artificial AnalysisGPT-4.1 nano Coding Index11,1
Artificial AnalysisGPT-4.1 nano GPQA Diamond51.2%
Artificial AnalysisGPT-4.1 nano HLE3.8%
Artificial AnalysisGPT-4.1 nano IFBench32.0%
Artificial AnalysisGPT-4.1 nano τ²-Bench Telecom17.3%
Artificial AnalysisGPT-4.1 nano AA-LCR20.3%
Artificial AnalysisGPT-4.1 nano τ-Bench Banking3.5%
Artificial AnalysisGPT-4.1 nano GDPval-AA0.0%
Artificial AnalysisGPT-4.1 nano CritPt0.0%
Artificial AnalysisGPT-4.1 nano LiveCodeBench32.6%
Artificial AnalysisGPT-4.1 nano Terminal-Bench Hard3.8%
Artificial AnalysisGPT-4.1 nano Terminal-Bench 2.13.7%
Artificial AnalysisGPT-4.1 nano MMLU-Pro65.7%
Artificial AnalysisGPT-4.1 nano AIME 202524.0%
Artificial AnalysisGPT-4.1 nano AIME23.7%
Artificial AnalysisGPT-4.1 nano MATH-50084.8%
Design ArenaGPT-4.1 nano Models Arena 3D Elo922
Design ArenaGPT-4.1 nano Models Arena Code Categories Elo961
Design ArenaGPT-4.1 nano Models Arena Data Visualization Elo891
Design ArenaGPT-4.1 nano Models Arena Game Development Elo969
Design ArenaGPT-4.1 nano Models Arena UI Component Elo911
Design ArenaGPT-4.1 nano Models Arena Website Elo971
Vals AIGPT 4.1 Nano AIME26.5%
Vals AIGPT 4.1 Nano CorpFin v242.1%
Vals AIGPT 4.1 Nano Finance Agent v12.5%
Vals AIGPT 4.1 Nano GPQA Diamond50.8%
Vals AIGPT 4.1 Nano LiveCodeBench42.7%
Vals AIGPT 4.1 Nano LegalBench61.1%
Vals AIGPT 4.1 Nano MATH 50080.2%
Vals AIGPT 4.1 Nano MedQA68.2%
Vals AIGPT 4.1 Nano MGSM69.3%
Vals AIGPT 4.1 Nano MMLU Pro63.5%
Vals AIGPT 4.1 Nano MMMU Pro55.1%
Vals AIGPT 4.1 Nano MortgageTax52.8%
Vals AIGPT 4.1 Nano TaxEval v260.8%

Aplicaciones

Aplicaciones públicas que envían más tráfico a este modelo. Una buena señal de cómo son las cargas de trabajo reales en producción, y una pista sobre los casos de uso para los que este modelo es más adecuado.

Actividad

Volumen de tokens y tráfico de solicitudes a este modelo a lo largo del tiempo.

API

Código listo para usar para llamar a este modelo. La API de OpenRouter es compatible con OpenAI: la mayoría de los SDK funcionan con solo cambiar la URL base. Lo único que cambia entre modelos es el identificador del modelo que aparece a continuación.

Actualmente no está disponible mediante el enrutamiento dentro de la región de la UE. Documentación de enrutamiento dentro de la región

Documentación

Guías, recetarios, artículos de blog y herramientas para desarrollar con OpenAI: GPT-4.1 Nano (batch) en OpenRouter.

  • Quasar Alpha and Optimus Alpha RevealPublicación del blog

Explorar más modelos

Modelos de IA con visión: LLM multimodales para la comprensión de imágenesColecciónClasificaciones de modelos de IAClasificación
0,05 US$0,20 US$0,0125 US$----
--
Pruebas de rendimiento de AutoExacto
GPQA DiamondTAU-BenchOpenAI50,8 %10,0 %

Aún no hay suficientes datos de tiempo de actividad para mostrar.

Cuando se produce un error en un proveedor ascendente, podemos recuperarnos enrutando la solicitud a otro proveedor que funcione correctamente, si los filtros de su solicitud lo permiten. Puede acceder mediante programación a los datos de tiempo de actividad de cada proveedor a través de la API de endpoints. Obtenga más información sobre nuestras opciones de equilibrio de carga y enrutamiento de proveedores.

Aún no hay suficientes datos sobre las aplicaciones que usan este modelo.

Preguntas frecuentes

For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million token context window, and scores 80.1% on MMLU, 50.3% on GPQA, and 9.8% on Aider polyglot coding – even higher than GPT‑4o mini. It’s ideal for tasks like classification or autocompletion.

La documentación de GPT-4.1 Nano (batch) en OpenRouter incluye la publicación del blog Quasar Alpha and Optimus Alpha Reveal. La guía de inicio rápido cubre las claves de API y su primera solicitud, y la referencia de la API enumera todos los parámetros.

GPT-4.1 Nano (batch) cuesta 0,05 US$/M de tokens de entrada y 0,20 US$/M de tókenes de salida, con tarifas independientes para Cache Read a 0,0125 US$/M tokens y Web Search a 10,00 US$/1K calls.

GPT-4.1 Nano (batch) tiene una ventana de contexto de 1.047.576 tókenes. Admite hasta 32.768 tókenes de respuesta.

Sí. GPT-4.1 Nano (batch) admite tools y tool_choice para llamadas a funciones. También admite salidas estructuradas mediante un esquema JSON en response_format.

GPT-4.1 Nano (batch) acepta imágenes, texto y archivos como PDF como entrada y devuelve texto.

GPT-6.1 Terra Pro, GPT-6.1 Terra, GPT-6 Luna Decisions y 58 más son otros modelos de texto de OpenAI.

GPT-4.1 Nano (batch) se lanzó el 14 de abril de 2025. Su fecha límite de conocimientos es 30 de junio de 2024.

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GPT-4.1 Nano (batch) cuesta 0,05 US/Mdetokensdeentraday0,20 US/M de tokens de entrada y 0,20 US/Mdetokensdeentraday0,20 US/M de tókenes de salida, con tarifas independientes para Cache Read a 0,0125 US/MtokensyWebSearcha10,00 US/M tokens y Web Search a 10,00 US/MtokensyWebSearcha10,00 US/1K calls.