Janus Pro 7B

Generación de imágenesDisponible
de DeepSeekID del modelo: janus-pro-7b

DeepSeek's unified multimodal model. Decouples vision encoding for both understanding and generation tasks.

Precio
≈ 0,0169 US$/ejecución
Entrada → Salida
Texto → Imagen
Desarrollador
DeepSeek
Actualizado
23 de septiembre de 2026
01

Playground

Probar Janus Pro 7B

Sin formulario de entrada

≈ 0,0169 US$/ejecución

Aún no hay formulario de entrada para este modelo

Sus entradas aún no están documentadas. Para que ninguna ejecución falle por una entrada incorrecta, no ofrecemos un formulario aquí. Elige un modelo comparable en su lugar.

02

Examples

Real outputs from the public examples of this model on Replicate, with the prompt and settings that produced them. They were not generated live on this page.
  • InputInput

    Prompt

    Convert the formula into latex code.

    Response

    Here is the formula in LaTeX code: \[ A_n = a_0 \left[ 1 + \frac{3}{4} \sum_{k=1}^{n} \left( \frac{4}{9} \right)^k \right] \]

  • InputInput

    Prompt

    explain this meme

    Response

    This image is a humorous meme that plays on the similarity in appearance between two individuals, one labeled "OpenAI" and the other "DeepSeek." Here's a detailed breakdown: 1. **Top Image (OpenAI)**: - The person is holding a firearm and appears to be in a shooting stance. - The label "OpenAI" is placed over the individual, suggesting that they are being humorously compared to the AI company OpenAI. 2. **Bottom Image (DeepSeek)**: - The person is also holding a firearm and in a similar shooting stance. - The label "DeepSeek" is placed over the individual, implying a humorous comparison to DeepSeek, a company known for its work in artificial intelligence and machine learning. 3. **Humor and Meaning**: - The meme humorously compares the two individuals based on their similar appearance and actions. - It plays on the idea that both OpenAI and DeepSeek are involved in AI research and development, and the meme creator is using the visual similarity to create a joke. 4. **Context**: - The image is likely taken from a sporting event, as indicated by the background and the seating. - The meme is a lighthearted way to highlight the similarities between the two entities, with no serious intent. In summary, the meme is a playful comparison between two individuals, using their visual similarity and the context of holding firearms to create a humorous joke.

  • InputInput

    Prompt

    explain this meme

    Response

    This image is a humorous meme comparing two concepts: "Decoupling Visual Encoding" and "Single Visual Encoder." 1. **Left Side: Decoupling Visual Encoding** - The image shows a muscular, strong-looking dog, representing a robust and powerful concept. - This symbolizes "Decoupling Visual Encoding," which implies a more efficient or effective way of encoding visual information. The muscular dog suggests strength, efficiency, and robustness in handling visual data. 2. **Right Side: Single Visual Encoder** - The image shows a smaller, less muscular dog, looking tired or less confident. - This represents "Single Visual Encoder," which suggests a simpler or less powerful approach to encoding visual information. The smaller dog implies that this method might not be as effective or robust as the decoupled approach. ### Overall Meaning: The meme humorously contrasts two concepts in the field of computer vision or machine learning, where "Decoupling Visual Encoding" is depicted as a more powerful and efficient method, while "Single Visual Encoder" is portrayed as less effective or less robust. The use of the Doge meme characters adds a layer of humor and relatability to the comparison.

03

Acerca de Janus Pro 7B

ResumenA fecha de 23 de septiembre de 2026

Janus Pro 7B es un modelo de DeepSeek en la categoría Generación de imágenes. En Railwail, Janus Pro 7B cuesta ≈ 0,0169 US$ por ejecución.

Fondo

Acerca de DeepSeek

Fundado en 2023 · Hangzhou, China

DeepSeek (深度求索) is a Chinese AI research lab founded in May 2023 in Hangzhou by Liang Wenfeng, the founder of the quant hedge-fund High-Flyer (which funds the lab). DeepSeek became globally prominent in late 2024 and early 2025 with the release of DeepSeek-V3 (Dec 2024), DeepSeek-R1 (Jan 2025) and the Janus multimodal family. The Janus series is DeepSeek's unified understanding-and-generation model: Janus (Oct 2024), JanusFlow (Nov 2024) and Janus Pro (Jan 2025) extend a single Transformer to both interpret images and generate them with a decoupled visual encoder design. All Janus models are open-sourced under a permissive license on Hugging Face and GitHub.

Visitar DeepSeek

Arquitectura

Unified autoregressive multimodal Transformer (understanding + image generation)

Janus-Pro-7B (January 2025) is the largest member of the Janus family from DeepSeek. The model unifies multimodal understanding and image generation in a single autoregressive Transformer, but uniquely decouples the visual encoders for the two tasks: a SigLIP-style ViT encoder is used for image understanding (so visual features are semantic), while a VQ tokeniser based on LlamaGen is used for image generation (so visual features are reconstruction-oriented). Both feature paths are projected to the same 7B LLM backbone, which generates either text or image tokens depending on the task. For image generation Janus-Pro produces 384x384 images by autoregressive sampling of VQ tokens which are then decoded by the LlamaGen decoder. Janus-Pro improves over Janus by scaling data to ~90M image-text pairs and adding a second stage of supervised fine-tuning. DeepSeek reports that Janus-Pro-7B beats DALL-E 3, SD3-Medium and SDXL on GenEval and DPG-Bench, despite being a much smaller and unified model.

Parámetros
7B parameters (Janus-Pro-7B)
Contexto
4096 tokens

Capacidades

  • Unified image understanding + image generation in one 7B model
  • Open weights under permissive DeepSeek license
  • Outperforms DALL-E 3 and SD3-Medium on GenEval (per DeepSeek paper)
  • 384x384 native generation resolution
  • Compatible with Hugging Face Transformers and vLLM
  • Useful for multimodal agents that both see and draw
  • Strong instruction-following thanks to LLM-style backbone
  • Best for: research, multimodal agents, prototyping unified pipelines, fine-tuning.

Entrenamiento y licencia

Pretrained on a mix of ~90M image-text pairs, text-only data and image-only data. Janus-Pro-7B adds extra supervised fine-tuning stages and a larger unified dataset compared to Janus 1B.

Licencia: DeepSeek Janus License — open weights, free for research and commercial use with attribution and standard restrictions.

Pruebas de seguridad: DeepSeek applies content filters and reports safety evaluations in the Janus-Pro technical report, but the open weights ship without integrated safety classifier.

Limitaciones conocidas

  • Only 384x384 native resolution — needs upscaler for production
  • Image quality below dedicated diffusion models like FLUX 1.1 [pro]
  • Open weights have no built-in safety filter
  • Autoregressive sampling is slower per pixel than diffusion at high res
04

Precios

Precios en dólares estadounidenses. El uso se cobra con créditos prepagados.
Ejecución típica (≈ 14 s en L40S)0,0169 US$ por ejecución
Tiempo de GPU (L40S)0,00117 US$ por segundo de GPU
  • Se factura por el tiempo de GPU que realmente tarda la ejecución. Cuando comienza la ejecución, se reserva 3× el precio típico de tu saldo y se liquida después.
  • 1 crédito = 0,01 US$

Calculadora de costes

Calculadora de precios

s

Típico según el proveedor: aprox. 14,4 s

Total

1,69 US$

169 créditos

Por ejecución

0,0169 US$ · 1,69 créditos

Se factura el tiempo real de GPU; este es un estimado.

05

API

Llama a Janus Pro 7B con tu clave API de Railwail. Usa este ID de modelo en la solicitud:

Sin ejemplo de API verificado

Las entradas de este modelo aún no están documentadas.

06

Especificaciones

ID del modelo
janus-pro-7b
Desarrollador
DeepSeek
Entrada
Texto
Salida
Imagen
Facturación
Por uso (tokens o tiempo de GPU)
Tamaño del modelo
7B parameters (Janus-Pro-7B)
Licencia
DeepSeek Janus License — open weights, free for research and commercial use with attribution and standard restrictions.
Entrada del catálogo actualizada
23 de septiembre de 2026

Etiquetas

  • deepseek
  • janus
  • open-weights
  • unified-multimodal
  • pricing-tbd
07

Casos de uso

Para qué se utiliza

  • Multimodal research and prototyping
  • Unified vision-language agents that draw + describe
  • Interactive image dialogue systems
  • Fine-tuning base for specialised generators
  • Educational demos of unified multimodal models
  • Visual question answering with generation
08

Preguntas frecuentes

¿Qué es Janus Pro 7B?

Janus Pro 7B es un modelo de DeepSeek en la categoría Generación de imágenes.

¿Cuánto cuesta Janus Pro 7B en Railwail?

En Railwail, Janus Pro 7B cuesta ≈ 0,0169 US$ por ejecución. Se te cobra por lo que cada solicitud realmente consume. El uso se paga con créditos prepagados; 1 crédito equivale a 0,01 US$.

¿Qué velocidad tiene Janus Pro 7B?

Aún no hay suficientes ejecuciones medidas de Janus Pro 7B en Railwail para indicar un tiempo de ejecución. Depende de la entrada, la configuración y la carga en el proveedor.

¿Es Janus Pro 7B mejor que FLUX 1.1 Pro?

Depende de la tarea. Janus Pro 7B (DeepSeek) y FLUX 1.1 Pro (Black Forest Labs) son ambos modelos en la categoría Generación de imágenes. La página de comparación muestra sus precios y especificaciones lado a lado.

Comparar Janus Pro 7B y FLUX 1.1 Pro
09

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    Comparar Janus Pro 7B vs. Icons (SDXL Flat Pop)
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    Comparar Janus Pro 7B vs. InstantID
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    Comparar Janus Pro 7B vs. Sticker Maker

Todos los modelos a través de una API

Una clave API para todos los modelos en Railwail. El uso se cobra desde créditos prepagados, 1 crédito = 0,01 US$.