Seedream 4.5 vs Nano Banana Pro: Can the SOTA Image Be Replaced

On December 3rd, ByteDance officially released the new generation AI image model, Seedream 4.5. In late August this year, shortly after Nano Banana burst onto the scene, ByteDance launched Seedream 4.0 with a precision strike. In the previous test, Seedream 4.0 outperformed Nano Banana in five out of six comparisons, achieving a comprehensive lead. Let’s recap the conclusions for the 4.0 version:

1. Overall visual quality has undergone a generational leap forward

2. Dual optimization of multimodal understanding and execution

3. Compared to Nano Banana, the biggest advantage is not just capability, but reliability

Now let’s look at the official update description for version 4.5:

Compared to the 4.0, Seedream 4.5’s core upgrade focuses on enhancing controllability, precision, and professional adaptability in generation. The model does not simply pursue breakthroughs in artistic effects but emphasizes optimizing the reliability, consistency, and practicality of generating content in commercial and professional contexts, enabling it to integrate more seamlessly into actual workflows. This upgrade has several highlights worth noting:

1. Multi-element Consistency Maintenance: In complex tasks involving multiple image references, element fusion, and multiple rounds of editing, the model demonstrates greater stability in preserving the core features and stylistic unity of subjects (such as characters, products, or logos). This significantly reduces randomness and distortion in generated outputs.

2. Professional Text Rendering & Layout: For design needs like posters and marketing materials, the model enhances the accuracy of text generation and the rationality of layout composition. It supports mixed Chinese-English typesetting, effectively addressing previous pain points in AI-generated images such as distorted text and chaotic layouts. This brings the results closer to a “ready-to-use” preliminary draft.

3. Spatial Logic & Physical Understanding: By strengthening its grasp of real-world common sense and spatial relationships, the model generates more reasonable and realistic complex scenes, perspective views, and specific materials (like fabric folds or paper textures). This expands its application potential in fields requiring precise representation, such as education and design.

4. Multi-image Referencing & Precise Instruction Following: The model supports simultaneous reference and analysis of up to 10 input images. It can also parse and execute complex text instructions more accurately, including specific demands for style, composition, and details. This provides users with a more efficient and controllable creative visualization tool.

302.AI has now integrated the Seedream 4.5 model API, allowing users to access it online via the API Mall. In our last comparative test with Nano Banana Pro, Seedream 4.0 suffered a clean sweep, losing all 6 cases. So the upgraded Seedream 4.5 comes back, will it continue to lag?

Case 1: Text-to-Image — Multi-Subject Street Photography

Test Points: Spatial Logic, Physical Understanding, Specified Style

*Note: Currently, the realism of human & object generation in flagship models has converged, so single portrait realism tests are basically no longer conducted

Prompt: Street photography in the style of Alex Webb. A complex, multi-layered composition at Times Square during the Thanksgiving Day Parade.

Foreground: A chaotic but artistic arrangement of people. A serious businessman in a dark suit is checking his watch, looking annoyed, standing right next to an ecstatic child sitting on a father’s shoulders reaching out towards the sky. An arm holding a half-eaten pretzel cuts into the frame from the side, adding depth.

Background: A massive, bright yellow Pikachu inflatable balloon floats high between the skyscrapers, framed by colorful confetti and billboard advertisements.

Lighting & Color: Harsh natural sunlight creating deep, geometric shadows (chiaroscuro). High saturation, vibrant colors (especially the yellow of Pikachu contrasting with deep reds and blacks of the crowd). Deep depth of field, everything in focus. 35mm film grain, Kodachrome aesthetic, decisive moment.

Character realism: Seedream 4.5 ★★★★★| Nano Banana Pro ★★★★★

Visual aesthetics: Seedream 4.5 ★★★★★| Nano Banana Pro ★★★

Prompt adherence: Seedream 4.5 ★★★★★| Nano Banana Pro ★★★★

Seedream 4.5 wins. The victory hinges on its superior ability to capture the requested photographic essence and its mastery of compositional detail. Seedream authentically delivered the “35mm film grain, Kodachrome” look, while Nano Banana Pro’s result felt sterile and digital. More importantly, Seedream constructed a coherent visual story: the left street lamp, the central interaction between Pikachu and the child, and the bread truck on the right create a balanced, engaging scene with clear spatial depth. This thoughtful composition highlights the gap between intentional photographic artistry and basic image generation. But both models failed equally in generating coherent text, an ongoing challenge in the field. One detail point is that Seedream’s output(entirely white people)lacked the crowd diversity present in Nano Banana Pro’s version, an area for potential improvement.

Case 2: Text-to-Image — World Knowledge — Modeling

Test Point: World Knowledge, Professional Graphic Rendering, 3D Modeling

Prompt: A realistic full-body portrait of a [ARTIST] in their signature style, positioned next to a giant vertical smartphone displaying a Spotify interface. The phone screen shows a music player interface featuring the song “[SONG]” with signature [COLOR] accent colors at approximately

*Using this template, we conducted 2 sets of celebrity generations. You can replace the characters and corresponding tracks as needed.

Character Accuracy: Seedream 4.5 ★ | Nano Banana Pro ★★★★★

Music Cover Accuracy: Seedream 4.5 ★ | Nano Banana Pro ★★★★

Modeling aesthetics: Seedream 4.5 ★★★★ | Nano Banana Pro ★★★★★

Nano Banana Pro wins this round. There’s not much to analyze, as it uses 2 top-tier celebrities that appeal to the masses. Just one question, how much data on Nana OuYang(Chinese singer, musician, and actress) has Seedream been trained on?

Case 3: Text-to-Image — Phone Photography

Test Point: Specifying style, world knowledge

Prompt: Candid smartphone photography, shot on iPhone 15, 26mm lens. A realistic, slightly unpolished eye-level shot of a high-end dinner in a private room.

Foreground: A chaotic but authentic tabletop scene. A bottle of Kweichow Moutai (15 Year Old, brown ceramic bottle) and a bottle of The Macallan 18 stand prominently among scattered cigarette packs and napkins. The table is covered with delicate Huaiyang cuisine (e.g., Lion’s Head meatballs, braised bamboo shoots), reflecting the local flavor.

Background (Jiangzhe Aesthetic): The setting is a refined “New Chinese” style private dining room inspired by Jiangnan gardens.

Furniture: Elegant dark solid wood furniture with Ming-style silhouettes.

Decor: In the background, intricate wooden lattice screens (geometric window patterns) divide the space, creating depth.

Details: A calligraphy scroll hangs on a textured white wall. Soft, warm ambient lighting glows from fabric lanterns, casting gentle shadows on the wood textures.

Atmosphere: The contrast between the messy, lively drinking session on the table and the serene, Zen-like wooden interior environment. Authentic color grading, realistic indoor lighting, no studio filters.

Object realism: Seedream 4.5 ★★★ | Nano Banana Pro ★★★★

Visual aesthetics: Seedream 4.5 ★★★★★ | Nano Banana Pro ★★★★

Prompt adherence: Seedream 4.5 ★★★★★ | Nano Banana Pro ★★★★★

Seedream 4.5 edges it out. Seedream’s environment has a stronger Jiangsu–Zhejiang aesthetic, with richer visual layers. The slightly overexposed scene outside the window looks quite realistic. Both models do well in object realism, but the accuracy is where points are deducted. The appearance of the “15-year” bottle is incorrect in both outputs — obviously fake at a glance. Also note that on Seedream’s Macallan 18, the triangular label on the neck actually says “15.” In text generation, the banana label text is clearer.

Case 4: Image-to-Image —Four-view image

Test point: World knowledge, professional image rendering, and layout

Prompt: Based on the vehicle in the image, create a four-view image of the components, and describe each important part in English

Vehicle accuracy: Seedream 4.5 ★★★★★ | Nano Banana Pro ★★★★★

Info Accuracy&Richness: Seedream 4.5 ★★ | Nano Banana Pro ★★★★★

Prompt adherence: Seedream 4.5 ★★★★★ | Nano Banana Pro ★★★★★

Nano Banana Pro wins. The information density is not on the same level. Seedream’s line indicators are mostly incorrect; for example, black alloy wheels (wheels) are pointed at the windows. What truly reflects Nano Banana Pro’s strength is the cockpit diagram in the lower right, which fully utilizes world knowledge, with details as fine as the air filter and brake fluid reservoir being labeled.

Case 5: Text-to-Image — Infographic

Test point: World knowledge, professional image rendering, and layout

Prompt: Create an infographic in a hand-drawn sketch style, depicting the relationships between the main characters of the first to fourth seasons of 《Stranger Things》 with the information written in Chinese.

Character accuracy: Seedream 4.5 ★ | Nano Banana Pro ★★★★★

Info Richness: Seedream 4.5 ★ | Nano Banana Pro ★★★★★

Prompt adherence: Seedream 4.5 ★★ | Nano Banana Pro ★★★★★

Nano Banana Pro is undeniably the winner. No matter whether you’ve watched the series or understand the character relationships, the sheer level of detail and the richness of information in the artwork alone are enough to make a judgment. What impresses me most about Nano Banana Pro’s image is the depiction of a reversed world in the center, and also reversing the letters “UPSIDE DOWN,” showing a lot of cleverness and design sense. *Note: Nano Banana Pro’s character relationships still have inaccuracies, such as Max not being sacrificed

Case 6: Image-to-Image — Fusion Image

Test points: Multi-image reference, consistency, professional image rendering, and layout

Prompt: Replace the character in Image 1 with the characters in Image2, 3, 4, and 5, while keeping the text and background elements in Image 1 completely unchanged

Multi-Character consistency: Seedream 4.5 ★★★★ | Nano Banana Pro ★★★★★

Image and text rendering consistency: Seedream 4.5 ★★★★ | Nano Banana Pro ★★★★

Visual harmony: Seedream 4.5 ★★★ | Nano Banana Pro ★★★★★

Nano Banana Pro wins again. From the perspective of multi-character consistency, Banana delivers more natural facial features, while Seedream shows noticeable distortion and stretching. The expressions appear stiff, the eye directions are inconsistent, and the overall result is far from a cover-grade photo. In terms of text–image rendering and layout, both perform at a similar level. The imperfections mainly lie in failing to crop the characters into a half-body shot and relying on auto outpainting for the background, which reveals obvious AI artifacts. Looking at overall visual coherence, Seedream darkened the tones on its own and shifted the characters toward the left, resulting in an unbalanced composition. Banana’s overall color tone and visual texture are much closer to the original magazine aesthetic.

Seedream 4.5 model test conclusions

First, let’s state the most core conclusion: currently, the SOTA of image models is still Nano Banana Pro — backed by the SOTA LLM Gemini 3 Pro, it provides world knowledge that crushes opponents, making image generation stable

Back to Seedream 4.5, this test included 6 battles with 2 small wins, and the winning points were very consistent: Aesthetics.

In the street photography and mobile photography cases, either pursuing “photographic aesthetics” or “realism,” Seedream’s lighting, layers, and composition genuinely impressed me.
But once world knowledge is involved — whether it’s pop culture like music and TV series, or more specialized domains such as automotive engineering — its shortcomings become obvious. It can follow the prompt, but what it captures is only the form, not the essence.

Aesthetics Master vs World Simulator, in fact, understanding this concept is enough to choose the appropriate model according to your needs:

For daily casual shots, photo editing, or even some artistic creativity, emotional cinematic shots, I believe Seedream can handle all of that just fine.
But when it comes to productivity-driven tasks — like building product UIs, creating knowledge graphs, or anything that demands precise knowledge, reliable information, and zero mistakes — go for the Nano Banana Pro, my friend.

Lastly, it reminds me of a legendary model in the field of aesthetics, Midjourney. When will you update?