Janus Pro 7B

AfbeeldingsgenereringBeschikbaar
van DeepSeekModel-ID: janus-pro-7b

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

Prijs
≈ US$ 0,0169/uitvoering
Invoer → Uitvoer
Tekst → Afbeelding
Ontwikkelaar
DeepSeek
Bijgewerkt
23 september 2026
01

Playground

Janus Pro 7B proberen

Geen invoerformulier

≈ US$ 0,0169/uitvoering

Voor dit model is nog geen invoerformulier beschikbaar

De invoeren zijn nog niet gedocumenteerd. Om te voorkomen dat een uitvoering mislukt door onjuiste invoer, bieden we hier geen formulier aan. Kies in plaats daarvan een vergelijkbaar model.

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

Over Janus Pro 7B

SamengevatPer 23 september 2026

Janus Pro 7B is een model van DeepSeek in de categorie Afbeeldingsgenerering. Op Railwail kost Janus Pro 7B ≈ US$ 0,0169 per uitvoering.

Achtergrond

Over DeepSeek

Opgericht 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.

DeepSeek bezoeken

Architectuur

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.

Parameters
7B parameters (Janus-Pro-7B)
Context
4.096 tokens

Mogelijkheden

  • 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.

Training & licentie

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.

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

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

Bekende beperkingen

  • 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

Prijzen

Prijzen in US-dollars. Het gebruik wordt in rekening gebracht via vooraf gekochte credits.
Typische uitvoering (≈ 14 s op L40S)US$ 0,0169 per uitvoering
GPU-tijd (L40S)US$ 0,00117 per GPU-seconde
  • Afgerekend wordt de GPU-tijd die de run werkelijk gebruikt. Wanneer de run start, wordt het 3-voudige van de typische prijs van uw saldo gereserveerd en later verrekend.
  • 1 credit = US$ 0,01

Kostencalculator

Prijscalculator

s

Typisch volgens de provider: ongeveer 14,4 s

Totaal

US$ 1,69

169 credits

Per run

US$ 0,0169 · 1,69 credits

Afgerekend wordt de werkelijke GPU-tijd; dit is een schatting.

05

API

Roep Janus Pro 7B aan met je Railwail API-sleutel. Gebruik deze model-ID in het verzoek:

Geen geverifieerd API-voorbeeld

De invoer van dit model is nog niet gedocumenteerd.

06

Specificaties

Model-ID
janus-pro-7b
Ontwikkelaar
DeepSeek
Invoer
Tekst
Uitvoer
Afbeelding
Facturering
Op basis van gebruik (tokens of GPU-tijd)
Modelgrootte
7B parameters (Janus-Pro-7B)
Licentie
DeepSeek Janus License — open weights, free for research and commercial use with attribution and standard restrictions.
Catalogusitem bijgewerkt
23 september 2026

Tags

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

Gebruiksscenario's

Waarvoor het wordt gebruikt

  • 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

Veelgestelde vragen

Wat is Janus Pro 7B?

Janus Pro 7B is een model van DeepSeek in de categorie Afbeeldingsgenerering.

Hoeveel kost Janus Pro 7B op Railwail?

Op Railwail kost Janus Pro 7B ≈ US$ 0,0169 per uitvoering. U betaalt voor wat elke aanvraag daadwerkelijk verbruikt. Gebruik wordt betaald met vooraf gekochte credits; 1 credit is gelijk aan US$ 0,01.

Hoe snel is Janus Pro 7B?

Er zijn nog niet genoeg gemeten runs van Janus Pro 7B op Railwail om een uitvoeringstijd op te geven. Dit hangt af van de invoer, de instellingen en de belasting bij de provider.

Is Janus Pro 7B beter dan FLUX 1.1 Pro?

Dat hangt van de taak af. Janus Pro 7B (DeepSeek) en FLUX 1.1 Pro (Black Forest Labs) zijn beide modellen in de categorie Afbeeldingsgenerering. De vergelijkingspagina toont hun prijzen en specificaties naast elkaar.

Janus Pro 7B en FLUX 1.1 Pro vergelijken
09

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Alle modellen via één API

Één API-sleutel voor elk model op Railwail. Gebruik wordt afgerekend via vooraf gekochte credits, 1 credit = US$ 0,01.