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Favicon de openai

OpenAI: gpt-oss-20b (batch)

openai/gpt-oss-20b:batch

Pesos del modelo
Comparar

gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for lower-latency inference and deployability on consumer or single-GPU hardware. The model is trained in OpenAI’s Harmony response format and supports reasoning level configuration, fine-tuning, and agentic capabilities including function calling, tool use, and structured outputs.

Modalidades
In / out price
0,024 US$ / 0,112 US$por 1M
Contexto
131K
Publicado
5 ago 2025
Fecha límite de conocimiento
jun 2024
Comparar
ProveedoresPreciosRendimientoTiempo de actividadPruebas de rendimientoAplicacionesActividadPreguntas 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-oss-20b (batch) (Artificial Analysis, Design Arena y Vals AI)
FuentePrueba de rendimientoPuntuación
Artificial Analysisgpt-oss-20b (High) Coding Index20,7
Artificial Analysisgpt-oss-20b (High) Agentic Index1,2
Artificial Analysisgpt-oss-20b (High) GPQA Diamond68.8%
Artificial Analysisgpt-oss-20b (High) HLE11.0%
Artificial Analysisgpt-oss-20b (High) IFBench65.1%
Artificial Analysisgpt-oss-20b (High) τ²-Bench Telecom60.2%
Artificial Analysisgpt-oss-20b (High) AA-LCR34.7%
Artificial Analysisgpt-oss-20b (High) τ-Bench Banking7.0%
Artificial Analysisgpt-oss-20b (High) GDPval-AA0.0%
Artificial Analysisgpt-oss-20b (High) CritPt1.4%
Artificial Analysisgpt-oss-20b (High) LiveCodeBench77.7%
Artificial Analysisgpt-oss-20b (High) SciCode38.9%
Artificial Analysisgpt-oss-20b (High) Terminal-Bench Hard10.6%
Artificial Analysisgpt-oss-20b (High) Terminal-Bench 4.00.0%
Artificial Analysisgpt-oss-20b (High) Terminal-Bench 2.113.9%
Artificial Analysisgpt-oss-20b (High) MMLU-Pro74.8%
Artificial Analysisgpt-oss-20b (High) AIME 202589.3%
Artificial Analysisgpt-oss-20b (Low) GPQA Diamond61.1%
Artificial Analysisgpt-oss-20b (Low) HLE5.3%
Artificial Analysisgpt-oss-20b (Low) IFBench57.8%
Artificial Analysisgpt-oss-20b (Low) τ²-Bench Telecom50.3%
Artificial Analysisgpt-oss-20b (Low) AA-LCR31.0%
Artificial Analysisgpt-oss-20b (Low) CritPt0.0%
Artificial Analysisgpt-oss-20b (Low) LiveCodeBench65.2%
Artificial Analysisgpt-oss-20b (Low) Terminal-Bench Hard4.5%
Artificial Analysisgpt-oss-20b (Low) MMLU-Pro71.8%
Artificial Analysisgpt-oss-20b (Low) AIME 202562.3%
Design ArenaGPT OSS 20B Models Arena Data Visualization Elo933
Design ArenaGPT OSS 20B Models Arena Website Elo852
Vals AIGPT OSS 20B AIME86.0%
Vals AIGPT OSS 20B CaseLaw v243.8%
Vals AIGPT OSS 20B CorpFin v253.1%
Vals AIGPT OSS 20B GPQA Diamond68.9%
Vals AIGPT OSS 20B LiveCodeBench80.4%
Vals AIGPT OSS 20B LegalBench70.8%
Vals AIGPT OSS 20B MATH 50094.2%
Vals AIGPT OSS 20B MedQA82.9%
Vals AIGPT OSS 20B MGSM89.0%
Vals AIGPT OSS 20B MMLU Pro71.6%
Vals AIGPT OSS 20B TaxEval v263.7%

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

Explorar más modelos

Clasificaciones de modelos de IAClasificación
0,024 US$0,112 US$----
--
ProveedorEntrada / Salida /M
RendimientoTiempo de actividad
  • Favicon de DeepInfra
    Entrada 0,024 US$ / Salida 0,112 US$
    Rendimiento --Tiempo de actividad --
Pruebas de rendimiento de AutoExacto
GPQA DiamondTAU-BenchDekaLLM68,5 %--SiliconFlow63,0 %--auto-routing66,7 %52,5 %Novita58,1 %--Darkbloom64,7 %51,1 %
+8 proveedores más

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

gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for lower-latency inference and deployability on consumer or single-GPU hardware.

gpt-oss-20b (batch) cuesta 0,024 US$/M de tokens de entrada y 0,112 US$/M de tókenes de salida.

gpt-oss-20b (batch) tiene una ventana de contexto de 131.072 tókenes. Admite hasta 131.072 tókenes de respuesta.

Sí. gpt-oss-20b (batch) admite tools y tool_choice para llamadas a funciones. También admite salidas estructuradas mediante un esquema JSON en response_format.

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

gpt-oss-20b (batch) se lanzó el 5 de agosto de 2025. Su fecha límite de conocimientos es 30 de junio de 2024.

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gpt-oss-20b (batch) cuesta 0,024 US/Mdetokensdeentraday0,112 US/M de tokens de entrada y 0,112 US/Mdetokensdeentraday0,112 US/M de tókenes de salida.