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OpenAI: gpt-oss-120b (batch)

openai/gpt-oss-120b:batch

Pesos del modelo
Comparar

gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized to run on a single H100 GPU with native MXFP4 quantization. The model supports configurable reasoning depth, full chain-of-thought access, and native tool use, including function calling, browsing, and structured output generation.

Modalidades
Precio de entrada / salida
0,0296 US$ / 0,136 US$por 1M
Contexto
131K
Publicado
5 ago 2025
Fecha de corte del 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-120b (batch) (Artificial Analysis, Design Arena y Vals AI)
FuentePrueba de rendimientoPuntuación
Artificial Analysisgpt-oss-120b (High) Coding Index30,4
Artificial Analysisgpt-oss-120b (High) Agentic Index3,7
Artificial Analysisgpt-oss-120b (High) GPQA Diamond78.2%
Artificial Analysisgpt-oss-120b (High) HLE19.6%
Artificial Analysisgpt-oss-120b (High) IFBench69.0%
Artificial Analysisgpt-oss-120b (High) τ²-Bench Telecom65.8%
Artificial Analysisgpt-oss-120b (High) AA-LCR52.0%
Artificial Analysisgpt-oss-120b (High) τ-Bench Banking12.8%
Artificial Analysisgpt-oss-120b (High) GDPval-AA5.8%
Artificial Analysisgpt-oss-120b (High) CritPt1.1%
Artificial Analysisgpt-oss-120b (High) LiveCodeBench87.8%
Artificial Analysisgpt-oss-120b (High) SciCode34.0%
Artificial Analysisgpt-oss-120b (High) Terminal-Bench Hard23.5%
Artificial Analysisgpt-oss-120b (High) Terminal-Bench 4.00.0%
Artificial Analysisgpt-oss-120b (High) Terminal-Bench 2.126.2%
Artificial Analysisgpt-oss-120b (High) MMLU-Pro80.8%
Artificial Analysisgpt-oss-120b (High) AIME 202593.4%
Artificial Analysisgpt-oss-120b (Low) Coding Index21,2
Artificial Analysisgpt-oss-120b (Low) GPQA Diamond67.2%
Artificial Analysisgpt-oss-120b (Low) HLE5.9%
Artificial Analysisgpt-oss-120b (Low) IFBench58.3%
Artificial Analysisgpt-oss-120b (Low) τ²-Bench Telecom45.0%
Artificial Analysisgpt-oss-120b (Low) AA-LCR46.0%
Artificial Analysisgpt-oss-120b (Low) τ-Bench Banking2.9%
Artificial Analysisgpt-oss-120b (Low) GDPval-AA0.0%
Artificial Analysisgpt-oss-120b (Low) CritPt0.0%
Artificial Analysisgpt-oss-120b (Low) LiveCodeBench70.7%
Artificial Analysisgpt-oss-120b (Low) Terminal-Bench Hard5.3%
Artificial Analysisgpt-oss-120b (Low) Terminal-Bench 2.113.9%
Artificial Analysisgpt-oss-120b (Low) MMLU-Pro77.5%
Artificial Analysisgpt-oss-120b (Low) AIME 202566.7%
Design ArenaGPT OSS 120B Models Arena 3D Elo898
Design ArenaGPT OSS 120B Models Arena Code Categories Elo961
Design ArenaGPT OSS 120B Models Arena Data Visualization Elo987
Design ArenaGPT OSS 120B Models Arena Game Development Elo992
Design ArenaGPT OSS 120B Models Arena UI Component Elo921
Design ArenaGPT OSS 120B Models Arena Website Elo966
Vals AIGPT OSS 120B AIME92.6%
Vals AIGPT OSS 120B CaseLaw v248.8%
Vals AIGPT OSS 120B CorpFin v258.2%
Vals AIGPT OSS 120B Finance Agent v1.121.5%
Vals AIGPT OSS 120B GPQA Diamond78.5%
Vals AIGPT OSS 120B LiveCodeBench83.2%
Vals AIGPT OSS 120B LegalBench75.9%
Vals AIGPT OSS 120B MATH 50094.8%
Vals AIGPT OSS 120B MedQA91.4%
Vals AIGPT OSS 120B MGSM92.0%
Vals AIGPT OSS 120B MMLU Pro79.2%
Vals AIGPT OSS 120B SWE-bench33.6%
Vals AIGPT OSS 120B TaxEval v271.6%
Vals AIGPT OSS 120B Terminal-Bench 2.019.1%

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
0,0296 US$0,136 US$----
--
Pruebas de rendimiento de AutoExacto
GPQA DiamondTAU-BenchAmazon Bedrock76,8 %--Amazon Bedrock76,8 %--Google72,6 %--AkashML77,4 %66,5 %Sail Research77,0 %66,7 %Near AI76,6 %66,8 %
+20 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-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized to run on a single H100 GPU with native MXFP4 quantization.

gpt-oss-120b (batch) cuesta 0,0296 US$/M de tokens de entrada y 0,136 US$/M de tókenes de salida.

gpt-oss-120b (batch) tiene una ventana de contexto de 131.072 tókenes. Admite hasta 131.072 tókenes de respuesta.

Sí. gpt-oss-120b (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-120b (batch) se lanzó el 5 de agosto de 2025. Su fecha límite de conocimientos es 30 de junio de 2024.

Más modelos de OpenAI

GPT-6.1 Terra Pro

GPT-6.1 Terra Pro is the same underlying model as GPT-6.1 Terra, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6.1 Terra and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6.1 Terra instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

TextoContexto de 1,1M1 US$ / 5 US$
GPT-6.1 Terra Pro (batch)

GPT-6.1 Terra Pro is the same underlying model as GPT-6.1 Terra, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6.1 Terra and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6.1 Terra instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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GPT-6.1 Terra

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GPT-6.1 Terra (batch)

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TextoContexto de 1,1M0,50 US$ / 2,50 US$
GPT-6 Luna Decisions

GPT-6 Luna Decisions is GPT-6 Luna served through OpenAI's Decisions API. Instead of generating text, it reads the content passed as state (text, JSON, or images) and returns typed, probabilistic answers to named questions in a single request: the probability of yes for a yes/no question (noul), a probability for every option plus the most likely one (choice), or a probability for every level of an ordered rubric plus the expected score (score).

It is built for classification, routing, moderation, and rubric grading where application code thresholds the returned numbers rather than parsing a chat reply. A request can carry up to 200 questions about the same content.

Decisiones0,10 US$ / 0 US$
GPT-6.1 Sol Pro

GPT-6.1 Sol Pro is the same underlying model as GPT-6.1 Sol, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6.1 Sol and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6.1 Sol instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6.1 Sol and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6.1 Sol instead.

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GPT-6.1 Sol

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GPT-6.1 Sol is an upgrade to GPT-6 Sol from OpenAI, positioned below the flagship GPT-6 Astra in the GPT-6 series. It is suited for agentic coding, computer use, document-heavy professional work, and multi-step business workflow automation, and approaches Astra-level results on these tasks at a much lower cost. Compared with GPT-6 Sol, it makes fewer factual errors and is more reliable at respecting explicit restrictions and user intent during agentic tasks.

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GPT-6 Luna Pro

GPT-6 Luna Pro is the same underlying model as GPT-6 Luna, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6 Luna and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6 Luna instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

TextoContexto de 1,1M0,10 US$ / 0,50 US$
GPT-6 Luna Pro (batch)

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Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6 Luna and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6 Luna instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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GPT-6 Luna (batch)

GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks, and at higher reasoning effort it can take on complex software engineering and computer-use tasks that previously called for a Sol-tier model. It shares the GPT-6 family's gains in factual reliability and its clearer, more concise communication style.

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GPT-6 Sol Pro

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Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6 Sol and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6 Sol instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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GPT-6 Sol Pro (batch)

GPT-6 Sol Pro is the same underlying model as GPT-6 Sol, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6 Sol and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6 Sol instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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GPT-6 Sol

GPT-6 Sol is the cost-efficient high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra and above the fast GPT-6 Luna tier. It is suited for demanding professional work, agentic coding, business workflow automation, and computer use, and is particularly strong at long-horizon software engineering tasks in real codebases. It approaches Astra-level factual reliability at a much lower cost and shares Astra's clearer, more concise communication style in technical and coding conversations.

TextoContexto de 1,1M2 US$ / 10 US$
GPT-6 Sol (batch)

GPT-6 Sol is the cost-efficient high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra and above the fast GPT-6 Luna tier. It is suited for demanding professional work, agentic coding, business workflow automation, and computer use, and is particularly strong at long-horizon software engineering tasks in real codebases. It approaches Astra-level factual reliability at a much lower cost and shares Astra's clearer, more concise communication style in technical and coding conversations.

TextoContexto de 1,1M1 US$ / 5 US$
GPT Astra Latest

This model always redirects to the latest model in the GPT Astra family.

TextoContexto de 1,1M
GPT Sol Latest

This model always redirects to the latest model in the GPT Sol family.

TextoContexto de 1,1M
GPT Terra Latest

This model always redirects to the latest model in the GPT Terra family.

TextoContexto de 1,1M

gpt-oss-120b (batch) cuesta 0,0296 US/Mdetokensdeentraday0,136 US/M de tokens de entrada y 0,136 US/Mdetokensdeentraday0,136 US/M de tókenes de salida.