In-Depth Analysis: How DeepSeek Janus Surpasses DALL-E 3

Happy New Year, friends! I wish you good health and success in the new year!

The wave of AI technology is continuously advancing, and 2025 is expected to be a year of explosive growth. I hope you keep an eye on the new technological industrial transformation in the coming year.

Recently, the Janus-Pro model launched by DeepSeek has sparked widespread discussion online. Whether it’s image analysis or text-to-image generation, this model has demonstrated astonishing capabilities. Even more surprisingly, it has comprehensively surpassed DALL-E 3 and Stable Diffusion in multiple authoritative tests, firmly sitting on the “throne” of the current image generation field. So, how exactly does Janus-Pro achieve this? What special meaning is hidden in its name? Let’s explore.

Why Is It Called Janus?

DeepSeek named this model “Janus” after the two-faced god Janus from ancient Roman mythology. Janus is the god of doors in Rome, symbolizing “transition and coexistence”; his two faces gaze at the past and the future, signifying connection and integration.

This imagery perfectly reflects the dual encoder architecture of the Janus model:

• Understanding Encoder (SigLIP), responsible for accurately analyzing image information and exploring the “past” of images.
• Generating Encoder (VQ Tokenizer), which generates high-quality images, creating the “future” of visuals.

Interestingly, the release of Janus-Pro coincided with Chinese New Year’s Eve, corresponding to the Chinese tradition of “posting door gods,” which is a clever cultural resonance, emphasizing the dual significance of protection and breakthrough that the model represents.

What Can Janus-Pro Do?

The core capabilities of Janus-Pro can be summarized as follows:

1. Image Analysis

Simply upload an image, and Janus-Pro can quickly analyze its content, providing detailed descriptions of regions, features, and more. Whether it’s natural landscapes or urban scenes, it can accurately capture key details, offering users comprehensive visual analysis.

2. Text-to-Image Generation

In the field of “text-to-image generation,” Janus-Pro shows astonishing expressiveness. Whether it’s color, texture, or semantic consistency, the images it generates are indeed artworks. Here are some official examples:

Aren’t they unbelievably beautiful? Not only that, Janus-Pro can also accurately understand complex textual descriptions, achieving multi-object generation, positional control, and other tasks.

Has It Already Surpassed DALL-E 3 and Stable Diffusion?

The answer is affirmative. According to the official test data released by DeepSeek, Janus-Pro has comprehensively surpassed DALL-E 3 and Stable Diffusion series in the two authoritative evaluations of GenEval and DPG-Bench. Here are the detailed data analyses:

GenEval Test: Comprehensive Superiority

In the GenEval test, Janus-Pro-7B achieved an overall score of **80%**, far exceeding DALL-E 3 (67%) and the Stable Diffusion series (74% and 43%). Particularly in color control and positional control tasks, Janus-Pro’s performance is especially outstanding:

• Color Control Score:
• 0.79 (Janus-Pro) > 0.43 (DALL-E 3) > 0.33 (SD3-Medium)
• Positional Control Score:
• 0.90 (Janus-Pro) > 0.83 (DALL-E 3) > 0.76 (SD3-Medium)

Although DALL-E 3 and SD3-Medium have slight advantages in multi-object generation and counting tasks, Janus-Pro excels in detail control and semantic consistency.

DPG-Bench Test: Optimal Performance

In the DPG-Bench test, Janus-Pro-7B scored slightly higher than DALL-E 3 and SD3-Medium, becoming the model with the best performance. The results of DPG-Bench indicate that Janus-Pro exhibits stronger understanding and generation capabilities when handling complex descriptions and generating semantically consistent images.

Strengths and Weaknesses Analysis: What Makes Janus-Pro Strong?

Strengths

1. Stronger Detail ControlJanus-Pro performs excellently in detail control tasks such as color and position, generating images that are delicate and aesthetically pleasing, suitable for high-demand creative design scenarios.

2. Higher Generation StabilityEven when faced with complex descriptions, Janus-Pro can still generate semantically consistent images, reducing the probability of “failure”.

3. Dual Task SupportJanus-Pro supports both image analysis and text-to-image generation, providing users with a comprehensive functional experience.

Weaknesses

1. Resolution LimitationsThe current version of Janus-Pro has a resolution limit of 384×384, which may not match DALL-E 3 and Stable Diffusion in high-resolution tasks (such as OCR, text recognition, etc.).

2. Multi-Object Generation Slightly InferiorAlthough Janus-Pro excels in details, there is still room for improvement in generating and counting complex multi-object scenes.

Future Outlook

The emergence of Janus-Pro has undoubtedly broken the long-standing dominance of DALL-E 3 and Stable Diffusion, especially setting a new benchmark in detail control and semantic consistency. In the future, if it can further enhance the resolution of generated images and combine stronger multi-object generation capabilities, it will undoubtedly be the absolute king of the next generation of image generation technology.

We also look forward to the domestic large model DeepSeek continuously optimizing Janus-Pro, bringing more surprises to creative design, visual arts, and other fields.

In the workplace, what do you think of the performance of the domestic large model Janus-Pro-7B? Feel free to leave comments for discussion!