Google Glitches | The Glossy World of Google AI Image Generation (Gemini Imagen with Nano Banana) – Great on the Outside, Bad on the Inside

Gemini Imagen by Google: A system between ambition and reality

The recent problems with Google Gemini and its integrated image generation engine, Imagen, raise serious questions about the reliability and transparency of Google's artificial intelligence. While the company is promoting its latest AI developments with great fanfare, behind the scenes, significant technical flaws and a questionable communication strategy toward users are becoming apparent.

Technical deficiencies in image generation

The current problems with Google Gemini manifest themselves at various levels. Users have been reporting fundamental malfunctions in the Imagen technology for weeks, particularly when generating images in the desired formats. The widespread problem primarily affects the creation of images in 16:9 format, which was previously possible without any problems, but is no longer implemented. Instead, the system only produces square images in 1024×1024 pixel format, even with explicit instructions for other aspect ratios.

Even more serious is the phenomenon where images are supposedly generated but cannot be displayed. Users receive confirmations that images have been successfully created, but only see empty spaces or error messages. This issue occurs in both the web version and the mobile app, rendering the image generation function virtually unusable.

The technical difficulties also extend to the API level. Developers report problems with the correct implementation of aspect ratios when using Imagen programmatically. Even when explicitly specifying the desired 16:9 format, images with different dimensions are generated, which significantly limits professional use.

Communication failure and lack of transparency

Google's handling of these apparent system errors is particularly problematic. The company doesn't proactively communicate these issues to users, even though they've been present for weeks. Instead, the system continues to claim that all functions are working properly, while actual performance is significantly degraded.

This lack of transparency is reinforced by Google's overall communication strategy. In its terms of service, the company explicitly warns against entering sensitive information, as all conversations can be analyzed by trained reviewers. At the same time, however, it lacks clear information about current system issues or planned maintenance.

The situation is exacerbated by Google's aggressive promotion of new features. While basic functions aren't working properly, the company continually presents new developments like "Nano Banana" or the latest updates with Gemini 2.5. This discrepancy between marketing and actual system performance leads to legitimate user frustration.

Historical patterns of problems

The current difficulties should not be viewed in isolation, but rather are part of a series of problems with Google's AI systems. In February 2024, Google had to completely disable the human representation in Gemini after the system generated historically inaccurate images. German soldiers were depicted with Asian facial features, and Vikings were given dreadlocks – errors that revealed fundamental problems in the training data preparation.

Google CEO Sundar Pichai admitted in an internal memo at the time that the company had "messed up." However, the promised structural improvements do not appear to have had the desired effect, as similar problems continue to arise in various forms.

The quality of text generation is also regularly criticized. Users report inconsistent responses, excessive wokeness, and a tendency to censor even harmless requests. In extreme cases, Gemini has even sent hateful messages to users, raising fundamental questions about system security.

At a time when a company's digital presence determines its success, the challenge is how to make this presence authentic, individual and far-reaching. Xpert.Digital offers an innovative solution that positions itself as an intersection between an industry hub, a blog and a brand ambassador. It combines the advantages of communication and sales channels in a single platform and enables publication in 18 different languages. The cooperation with partner portals and the possibility of publishing articles on Google News and a press distribution list with around 8,000 journalists and readers maximize the reach and visibility of the content. This represents an essential factor in external sales & marketing (SMarketing).

More about it here:

• Authentic. Individually. Global: The Xpert.Digital strategy for your company

Structural problems in development

The recurring problems point to systemic weaknesses in Google's AI development. The company appears to be under enormous time pressure to keep pace with competitors like OpenAI, resulting in hastily released products. This "move fast and break things" mentality may work in other areas of technology, but it proves problematic with AI systems, as errors have a more direct impact on the user experience.

The working conditions of the subcontractors responsible for content moderation and system improvement further exacerbate these problems. Reports of time pressure, low wages, and a lack of transparency in the supply chain raise doubts about the quality of manual system optimization.

Furthermore, the lack of integration between various Google services reveals structural deficiencies. While Google Photos is gaining new AI image processing features, basic image generation in Gemini isn't working properly. This fragmentation indicates insufficient internal coordination.

Impact on users

The problems described have concrete impacts on various user groups. Content creators and marketing professionals who rely on reliable image generation must resort to alternative solutions. This not only leads to workflow interruptions but also to additional costs for other tools.

The situation is particularly problematic for users of the paid Gemini Pro version. They pay for advanced features but often receive worse performance than promised. Many have already canceled their subscriptions because the promised improvements have not materialized.

The system's unreliability is also leading to a loss of trust in Google as an AI provider. Users who rely on the accuracy and availability of its services are increasingly turning to alternative providers. This could weaken Google's position in the highly competitive AI market in the long term.

Comparison with the competition

Gemini's problems become even more apparent when compared to competing systems. While OpenAI's DALL-E and Anthropic's Claude deliver more consistent results, Google struggles with fundamental functional issues. What's particularly striking is that even free alternatives often perform more reliably than Google's premium offerings.

While the image quality of Imagen 3, when it works, is praised, its frequent failures negate these technical advantages. Users demand reliability above all else, not sporadic peak performance.

Google also lags behind its competitors in terms of transparency. While other providers actively inform about system issues and announce maintenance windows, Google remains silent about known problems and leaves users in the dark about the causes of malfunctions.

Economic consequences

The ongoing problems also have economic repercussions for Google's business model. The company invests billions in AI development, but cannot realize the promised returns if the systems are unreliable. Gemini's cannibalization of the traditional search engine further exacerbates this problem.

At the same time, reputational damage is occurring, which could have a long-term impact on Google's market position. In a market where trust and reliability are crucial, repeated system outages and a lack of communication can cause lasting damage.

The costs of fixing the issues and implementing better quality assurance measures are likely to be significant. At the same time, Google must continue to invest in new developments to avoid falling further behind its competitors.

Regulatory and ethical aspects

The problems described also raise regulatory questions. The European Union is working on comprehensive AI regulations, and Google's lack of transparency could lead to stricter requirements. In particular, the use of user data for system improvements without clear communication about problems could have data protection consequences.

The discrepancy between Google's public statements about AI safety and the actual system performance is also ethically problematic. When basic functions fail to work reliably, the question arises as to the company's responsibility to its users.

The working conditions of the subcontractors responsible for system improvements raise additional ethical questions. Low wages and excessive time pressure could compromise the quality of manual reviews and thus jeopardize system security.

Necessary improvements

To regain user trust, Google must make fundamental changes to its approach. First, more transparent communication about system issues and planned maintenance is required. Users have a right to know when features aren't working properly.

In addition, Google should revise its quality assurance processes. The repeated issues indicate that current testing practices are inadequate. Greater integration between different teams and products could help resolve fragmentation issues.

Subcontractors' workplace quality must also be improved to ensure that manual system optimization is performed properly. This could incur higher costs but is necessary for long-term system quality.

Finally, Google should communicate realistic expectations instead of making exaggerated promises. Honesty about current limitations would build trust and encourage realistic usage scenarios.

The current problems with Google's Gemini and Imagen clearly demonstrate the challenges involved in developing and deploying complex AI systems. While the technical capabilities are impressive, implementation often fails due to fundamental issues such as reliability, transparency, and user communication. Only by returning to these fundamentals can Google secure its position in the AI ​​market long-term and regain the trust of its users.

Where can I use Nano Banana?

The most important information up front: Nano Banana is already integrated into gemini.google.com and accessible via several different platforms. There's no separate tool; the technology is built directly into Google's existing services.

1. Google Gemini App (Mobile & Web)

• Main access method: The easiest method is via the Gemini app on Android or iOS, or via gemini.google.com in the browser.
• Availability in Germany: Nano Banana has been available in Germany since August 26, 2025 and can be used free of charge.

2. Google AI Studio (developer platform)

• Professional access: Access advanced features via aistudio.google.com.

3. Vertex AI (Enterprise Solution)

• For enterprises: Google Cloud's Vertex AI offers Nano Banana for enterprise applications.

4. Third-party integrations

• Adobe Firefly: Creative Cloud users get unlimited generations with Nano Banana.
• Imogen App: iOS/macOS app with improved user interface and no watermark.
• Freepik: Access Nano Banana through the Freepik platform with affordable pricing.

Nano Banana isn't a separate tool, but a fully integrated feature of Google Gemini. The easiest way to access it is directly via gemini.google.com or the Gemini app, where you can start editing images immediately and for free. For professional applications, advanced options are available via AI Studio and Vertex AI.

What is Nano Banana?

The most important thing to note first: "Nano Banana" is simply the unofficial codename for Google's Gemini 2.5 Flash image model. It's a different model than Imagen, although both were developed by Google for image generation.

Nano Banana is the community nickname for Gemini 2.5 Flash Image, Google's latest AI image processing and generation model. The model initially took the top spot on the benchmark site LMArena.ai under this mysterious codename before Google officially introduced it as part of the Gemini family in August 2025.

Main features of Nano Banana (Gemini 2.5 Flash Image):

• Image processing and generation: The model enables precise image manipulation through natural language, including adding, removing, or modifying image elements.
• Character consistency: Particularly strong in the consistent representation of people or objects across multiple editing steps.
• Multi-image processing: Can understand multiple input images and merge them into a new image.
• World Knowledge Integration: Uses Gemini's comprehensive world knowledge for realistic image generation and processing.

What is Gemini Imagen?

Imagen is a separate series of text-to-image models developed by Google DeepMind. The current version is Imagen 4, launched in June 2025.

Main features of Imagen:

• Photorealism: Specialized in the creation of high-quality, photorealistic images.
• Text display: Particularly strong when displaying text in images.
• Artistic styles
• : Excellent for specific artistic styles such as impressionism or anime.
• Higher resolution: Creates images with up to 2048px resolution.

Key differences

Technical basis

• Nano Banana (Gemini 2.5 Flash Image): Based on the Gemini architecture, it is part of the multimodal Gemini system, which can process text and images in a conversation.
• Imagen: Uses diffusion models with cascaded upsampling stages (64×64 → 256×256 → 1024×1024).

Main areas of application

Nano Banana

• Conversational image editing
• Character consistency across multiple edits
• Multi-image composition
• Fast, context-aware image generation

Image

• Highest image quality and photorealism
• Specialized image processing tasks
• Professional applications such as logo design
• Precise text representation in images

Practical application recommendations

Choose Nano Banana if:

• Context and consistency are important
• You need iterative, conversational image editing
• Fast results with moderate quality are sufficient
• Character consistency across multiple images is required

Choose Imagen if:

• Highest image quality is our top priority
• Photorealistic results are required
• Professional applications or branding are in focus
• Precise text representation in images is required

Nano Banana (Gemini 2.5 Flash Image) and Imagen are two different approaches from Google for AI-based image generation. While Imagen focuses on maximum image quality and photorealism, Nano Banana focuses on conversational editing, character consistency, and the integration of Google's world knowledge. The choice between the two depends on the specific requirements of your project: quality versus contextual understanding and editing flexibility.

☑️ Our business language is English or German

☑️ NEW: Correspondence in your national language!

 

I would be happy to serve you and my team as a personal advisor.

You can contact me by filling out the contact form or simply call me on +49 89 89 674 804 (Munich) . My email address is: wolfenstein ∂ xpert.digital

I'm looking forward to our joint project.

 

 

☑️ SME support in strategy, consulting, planning and implementation

☑️ Creation or realignment of the digital strategy and digitalization

☑️ Expansion and optimization of international sales processes

☑️ Global & Digital B2B trading platforms

☑️ Pioneer Business Development / Marketing / PR / Trade Fairs

Xpert.Digital has in-depth knowledge of various industries. This allows us to develop tailor-made strategies that are tailored precisely to the requirements and challenges of your specific market segment. By continually analyzing market trends and following industry developments, we can act with foresight and offer innovative solutions. Through the combination of experience and knowledge, we generate added value and give our customers a decisive competitive advantage.

More about it here:

• Use the 5x expertise of Xpert.Digital in one package - starting at just €500/month