Nano Banana 2.1 on Anyken: compare the model examples with your intended input and output. Review the capabilities documented below, then use the controls actually offered in the workspace. Available settings and credits are shown before submission.
Official documentation
This section covers the core identity of this model, its position within the Gemini model family, and its technical specifications for input and output processing.
This model (gemini-nano-banana-2.1) is Google's latest high-efficiency image generation and conversational editing model. It represents a significant update to Nano Banana 2, maintaining Flash-level speed and cost efficiency while delivering notable improvements across several key areas. The model enhances visual quality and realism across 1K, 2K, and 4K output resolutions, with 1K being the default. A critical fix addresses tiling artifacts on wide and panoramic aspect ratios, specifically 1:4, 4:1, 1:8, and 8:1, at 2K and 4K resolutions. Text rendering and infographic layout accuracy have also been improved, making the model more suitable for content that combines visuals with text elements. These updates position this model as the recommended choice for new projects requiring efficient yet high-quality image generation.
The model accepts a variety of input data types, including text, image, video, and PDF, and produces both image and text outputs. It features a substantial input token limit of 131,072 tokens and an output token limit of 32,768 tokens, allowing for complex prompts and detailed generations. The model supports multi-image fusion with up to 14 reference images, enabling character consistency for up to 4 characters and object fidelity for up to 10 objects. This makes it suitable for tasks requiring consistent visual elements across multiple generations. The model code is gemini-nano-banana-2.1, and it is documented as a stable version with the latest update in October 2026.
This section details the specific capabilities of this model, including its support for image generation, search grounding, and configurable thinking levels, as well as its limitations.
This model supports image generation from text prompts and conversational editing where images are provided alongside text instructions. A key capability is multi-image fusion, which allows the model to process up to 14 reference images simultaneously. This feature supports character consistency for up to 4 characters and object fidelity for up to 10 objects, enabling the creation of coherent visual narratives or maintaining specific visual elements across multiple outputs. The model also supports grounding with Google Web and Image Search, which can inform the generation process with real-world information. All generated images include a SynthID watermark for responsible AI deployment.
The model's capabilities are clearly defined, with several features explicitly not supported. Supported features include image generation, search grounding, and configurable thinking levels. However, the model does not support audio generation, caching, code execution, file search, function calling, grounding with Google Maps, the Live API, structured outputs, or URL context. This focused feature set aligns with its role as a high-efficiency workhorse model, prioritizing core image generation tasks over broader multimodal or interactive capabilities. Users should consult the official documentation for the most current list of supported features and any updates.
This section outlines how to access this model through the Gemini API, including consumption options and the model's documented availability status.
This model is available through the Gemini API. The model supports the Batch API for efficient processing of multiple requests. It does not support Flex inference or Priority inference. Users can interact with the model using various programming languages, including Python, JavaScript, Java, and Go, as well as through REST API calls. The model is identified by the code gemini-nano-banana-2.1. For detailed implementation examples and best practices, users should refer to the official Image generation documentation provided by Google.
Google lists gemini-nano-banana-2.1 as a stable version and dates its latest update to October 2026. That version label identifies the documented release; performance in a particular application still needs evaluation. The image generation guide recommends this release for new projects instead of Nano Banana 2. Check the official model documentation when choosing a version or planning a migration.
This section describes the configurable aspects of this model, including output resolution, aspect ratio handling, and thinking levels, allowing users to tailor the model to their specific needs.
This model supports output resolutions of 1K, 2K, and 4K, with 1K being the default. The model includes specific fixes for tiling artifacts on wide and panoramic aspect ratios, including 1:4, 4:1, 1:8, and 8:1, at 2K and 4K resolutions. This makes it particularly suitable for generating images for banners, presentations, or other wide-format content. Users can select the resolution that best balances quality and computational cost for their specific use case. The availability of multiple resolutions provides flexibility for different output requirements.
The model supports configurable Thinking levels, which are documented as minimal, medium (default), and high. These settings allow users to experiment with different levels of processing depth for image generation tasks. The medium setting is the default configuration. Users are encouraged to evaluate the different thinking levels to understand how they affect the output for their specific prompts and use cases. The official documentation provides the definitive list of available settings without prescribing specific recommendations for particular tasks.
This section provides practical context for using this model, including comparisons with related models and guidance on accessing official resources.
This model is positioned as the primary high-efficiency workhorse model within the Nano Banana family. It is an update to Nano Banana 2 and is recommended for new projects. For tasks where speed and cost are the primary constraints, Nano Banana 2 Lite offers the fastest and cheapest option, though it is not optimized for multiple reference inputs or multi-turn sequential editing. For the most complex visual tasks requiring the highest level of world knowledge and precision creative control, Nano Banana Pro is the premium choice. Understanding these distinctions helps users select the most appropriate model for their specific requirements.
For comprehensive information on features, capabilities, and implementation, users should consult the official Google documentation. The Image generation page provides full coverage of features and capabilities for all Nano Banana models. The Gemini API documentation offers detailed specifications, code examples, and best practices. Users can also explore the AI tools directory on this site for related resources. The official model page at ai.google.dev is the authoritative source for the most current information, including any updates to supported features, configurations, or availability.
Common questions about this model, its capabilities, and how it compares to other models in the Gemini family.
Nano Banana 2.1 is Google's latest high-efficiency image generation and conversational editing model. It is an update to Nano Banana 2, offering improved visual quality, text rendering, and multi-turn consistency while maintaining Flash-level speed and cost efficiency. It supports resolutions up to 4K and includes fixes for tiling artifacts on panoramic aspect ratios.
Key improvements include enhanced visual quality and realism across 1K, 2K, and 4K resolutions, fixed tiling artifacts on wide aspect ratios, improved text rendering and infographic layout accuracy, and support for multi-image fusion with up to 14 reference images for character and object consistency.
The official guide positions this release as the efficient workhorse. Nano Banana 2 Lite is the speed-and-cost choice and is not optimized for multi-reference or sequential editing. Nano Banana Pro is the premium option for complex visual tasks, world knowledge and precise creative control.
