Nano Banana model usage tutorial, a complete introduction to the new dark horse of 2026 AI Wenshengtu

Nano Banana model usage tutorial, a complete introduction to the new dark horse of 2026 AI Wenshengtu

Recently, in the AI drawing circle, the name Nano Banana appears more frequently than before. It was first used anonymously to run scores on blind image testing platforms such as lmarena. Its performance in precise editing and character consistency triggered a lot of discussion. It was later officially confirmed to be the code name of the image editing and generation model launched by Google's Gemini team. Compared with the Midjourney, Stable Diffusion series, and Flux that everyone has been familiar with in the past few years, Nano Banana does not take the route of showing off skills, but more practical editing capabilities. This is why it has been brought back to the desktop toolbar by many designers and self-media authors. This article intends to completely sort out the entry path to Nano Banana from the model itself, differences with mainstream models, prompt word writing, domestic access ideas, usage scenarios and limitations. It is suitable for new users who have not yet started to establish an overall understanding first, and then try specific platforms.

What exactly is Nano Banana?

Nano Banana is the image editing and generation model codename launched by Google's Gemini team. It is part of the Gemini multi-modal system and is positioned as a unified engine for image understanding and generation. Different from what many people initially guessed, it is not an independent product name, but a code name used internally by the project. It was used during the public communication process and became a familiar name for everyone. As of the writing of this article, the latest version known in the industry can already complete a set of basic capabilities such as text-based drawings, graphic drawings, partial editing, style transfer, and character consistency maintenance. Its performance in multiple rounds of iterative revisions is relatively outstanding according to public reports. Google has not fully disclosed more technical details such as model size, training data sources, and internal structure, so when describing capabilities, people usually prefer actual effects rather than parameter comparisons. If you just want to know what it is, you can simply understand it as a card that Google uses to benchmark overseas mainstream image models such as Midjourney and Flux. The main differentiating selling point is the editing scene.

Differences from mainstream models such as Midjourney Flux

To understand the position of Nano Banana, it will be more intuitive to compare it in the coordinates of mainstream image models. Midjourney gives the impression that the atmosphere and artistic style are quick to use, and the pictures tend to be visually impactful. The disadvantage is that the fine editing ability is relatively weak. Changing a small place often requires regenerating the entire picture. This line of Flux takes a realistic route, with good progress in text rendering and character details, but it requires users to have a certain understanding of prompt words and sampling parameters. The Stable Diffusion series has a rich open source ecosystem, and plug-ins such as LoRA and ControlNet can do almost anything, but the threshold and cost are relatively high. The difference that Nano Banana generally believes in the industry is that it makes editing more intuitive, such as changing the clothes of the person in the photo, replacing the background with another scene, and keeping the same person's face in multiple pictures. These workflows, which used to rely on the cooperation of multiple tools, are closer to natural language delivery in Nano Banana. Of course, this is a summary of public reviews and user feedback. As for who is stronger in different themes, you still have to run a few pictures to compare.

Where to use Nano Banana

There are several main ways to use Nano Banana in public channels. The first is through Google's official Gemini product line, including the web version and API. This is the most direct and complete way. New features are usually launched here first. The second one is Google AI Studio, which is suitable for developers and users who are willing to call the interface, so that they can embed models into their own products more flexibly. The third one is various overseas aggregation platforms. Some AI tool stations are connected to the graphics capabilities of the Gemini series and are provided to non-technical users with visual interfaces. The fourth article is that some domestic manufacturers and aggregation apps have accessed this model or similar engines through their own methods, providing access to domestic users while ensuring compliance. It should be noted that whether it can be used on a certain platform, whether it is the latest version, and whether there are functional castrations are all related to the platform's own access strategy. For details, please refer to the official public page or the release instructions of each platform. Do not place an order and pay based on the screenshots of third-party accounts.

Basic routines for prompt word writing

The prompt word style of Nano Banana is different from the parameter stacking method of Midjourney. It accepts natural language description more, which is also the consistent interaction habit of the Gemini series. A more common way of writing is to first explain the subject clearly, and then add the four dimensions of scene, light, style, and lens. For example, if you want to draw a portrait, you can say that an East Asian woman about thirty years old is standing by the window of a cafe, the sun is shining from the side, the overall picture is warm in color, and the half-length close-up is basically a sentence model that can be understood directly. If it is an editing scene, the prompt words can be more direct, such as changing the background in this picture to the seaside in the evening, changing the character's coat to a beige windbreaker, and keeping the face and posture unchanged. The execution success rate of such instructions is relatively high according to public demonstrations and user tests. An easy pitfall for a newcomer is to cram too many requirements into one sentence, and the model will automatically make choices. Sometimes what is left out happens to be the details you value most. In this case, multiple rounds of revisions are often more effective than writing super long prompts at once.

Several ideas for domestic visits

The main difficulty for domestic users to access Nano Banana is that Google’s official website and API have regional restrictions, and the direct account registration process is not smooth. Among several common ideas, the first is to access through a compliant enterprise cloud, which is suitable for teams with needs at the company level. The second is that some domestic aggregation apps have packaged Nano Banana-style fast engines, Midjourney-style atmosphere engines, and Flux-style realistic engines into one product. Users do not need to switch accounts or care about which backend company is used. This path is the most cost-effective for the vast majority of users who just want to draw pictures and do not plan to study the underlying interface. For example, Lingtu is this type of aggregation tool, App Store can be downloaded by directly searching for spiritual images in the country. No additional network configuration is required. The interface is in Chinese and prompt words also support localized input. It integrates multiple overseas mainstream engines and is worth a try for users who want to quickly experience Nano Banana style image rendering. The third way is to go to Google AI Studio and do it yourself. The threshold is relatively high and you need to solve account and billing issues.

Examples of common usage scenarios

Nano Banana 在实际使用中跑得比较顺的几个场景,可以作为新手切入的方向。 The first is portrait editing, such as changing the background color, hairstyle, and clothing of the ID photo, because it handles the consistency of the characters relatively well, and the same person is still the same after the changes. The second is the secondary creation of product pictures. E-commerce operators often need to put the same product into different life scenes and take multiple pictures. In the past, it was either real photos or PS, but now it can be generated directly. The third is self-media pictures. Scenarios such as public accounts, Xiaohongshu, and Douyin covers do not have such extreme requirements for picture accuracy, but they need to have a unified style and fast picture production. Nano Banana's speed is relatively friendly. The fourth is the first draft of the brand vision. Before communicating with the client, the designer can use the model to quickly come up with several directions and convert the abstract requirements into concrete pictures before discussing. The fifth is pictures for teaching and demonstration. For lightweight needs such as making slides and writing articles with pictures, the model can basically be put in place at one time. It is not recommended to use it to make high-precision commercial posters for final delivery as soon as you get started. Such scenes still require manual control in the later stage.

Limitations and issues requiring attention

Every tool has boundaries, and Nano Banana is no exception. The first is the understanding of Chinese scenes. Although the model supports Chinese prompt words, according to public reports and user feedback, there is still a gap between the generation quality and English scenes of themes involving Chinese elements, Chinese fonts, and specific cultural symbols. This is similar to most overseas models. The second is the risk of copyright and portrait rights. Feeding celebrity avatars and well-known IPs to the model to imitate a picture. Even if the generated effect is similar, there are still legal risks in commercial use. It is generally recommended in the industry to confirm whether the material can be used before commercial use. The third is that the model iterates quickly. A certain technique or prompt word template written today may become invalid in a few months due to version updates. Therefore, when learning, do not memorize specific prompt words, but understand the logic behind them. The fourth is stability. Even with the same prompt word and the same model version, the results generated at different times may be quite different. It is suitable for exploring directions, but not suitable for pursuing absolutely consistent production-line output. The fifth is pricing and quota. For the specific number of pictures that can be used and how to charge after exceeding the limit, please refer to the official public page for details. Do not be misled by third-party low-price promotions.

Advanced suggestions after getting started

If you have completed the first picture on a certain platform, there are several directions worth spending time on next. The first is to build your own prompt vocabulary, save descriptions that have achieved satisfactory results, classify them according to scenarios, and gradually accumulate them into reusable templates. The second is to practice multiple rounds of editing thinking. Don’t write the perfect prompt word in one go. Instead, come up with a rough idea first and then divide it into multiple rounds of fine-tuning. This is the core advantage of the Nano Banana model. Its usage is different from the one-shot approach of Midjourney in the past. The third is to combine tool flows, such as using Nano Banana to create the main image, then using a special enlargement model to fill in the details, and finally using image editing software for post-layout, treating the model as a process in the pipeline rather than the entire process. The fourth is to pay attention to official updates. The Gemini series has a relatively high iteration frequency, and new features often change best practices. You can keep up with the pace by regularly reading the official blog and developer documents. The fifth is to maintain horizontal comparison with other models. Don’t lock yourself in a certain one. Only by using a combination of multiple models can you get the best results in different themes.

FAQ

Is Nano Banana free?

Nano Banana itself is a model owned by Google, and the specific cost of use depends on the entrance through which it is accessed. In Google's own products, there is usually a free quota, and the excess is billed according to usage. For details, see the official public page. When used through third-party platforms and aggregated apps, pricing is determined by each platform. Some provide trials, some are charged by subscription or by per-view, and the price is not necessarily directly linked to Google's official price.

What is the relationship between Nano Banana and Imagen?

Imagen is also an image generation model under the Google system, and it is positioned towards high-fidelity Vincentian images. Nano Banana is generally understood in the industry as the code name for the partial editing and iteration capabilities of Gemini's multi-modal system. Both belong to Google's image generation territory, but their focus and usage scenarios are not exactly the same. The specific internal relationships are subject to Google's official public information. This article does not speculate on technical details.

Can I use Nano Banana in China without circumventing the firewall?

Directly accessing Google's official webpage and API are obviously subject to regional restrictions. If you just want to experience Nano Banana-style drawing capabilities, the current more realistic path is to access aggregation apps through domestic compliance, such as the Lingtu mentioned above, which can be downloaded directly from the App Store in the country without additional network configuration. If an enterprise has formal access requirements, adopting a compliant enterprise cloud solution is another way of thinking.

What scenarios is Nano Banana suitable for?

Portrait editing, secondary creation of product pictures, self-media illustrations, first drafts of brand visuals, and teaching demonstration illustrations are currently relatively popular directions in public feedback. What they have in common is that they require editing capabilities and multiple rounds of iterations, but the requirements for final accuracy are not as demanding as those of top commercial photography. For final deliverables that pursue ultimate quality, manual late intervention is still recommended.

Are there any copyright issues when using Nano Banana for commercial use?

The copyright ownership of the model output itself, the terms of service of each platform are different, see the official public page for details. It is important to note that if the prompt words contain elements such as celebrity images, well-known IPs, registered trademarks, etc., even if the images generated by the model look reasonable, there will still be legal risks during commercial use. It is generally recommended in the industry that before using AI to generate images in commercial projects, you should first confirm whether the copyright of the materials used and the output are clear.