NANO BANANA PRO

Nano Banana Pro (also known as Nano Banana 2 and officially as Gemini 3 Pro Image) is Google’s latest state-of-the-art image generation and editing model, delivered in partnership with fal.ai. This AI model is designed for advanced, commercial-grade image editing and creative generation tasks by leveraging multimodal understanding and semantic reasoning, setting it apart from conventional image editing tools.

Core Capabilities Nano Banana Pro specializes in transforming and refining images using natural language prompts, without manual image masking or the need for layered editing. The model can understand context-rich instructions such as “make the sunset more dramatic while preserving the original mood,” performing nuanced edits that respect the integrity of the composition, including object relationships, lighting, and scene coherence.

Key capabilities include:

• Natural Language Editing: Apply complex edits by simply specifying your intent in conversational language. The model interprets object relationships, colors, and context, executing meaningful edits while maintaining coherence.
• Batch Editing and Variations: Generate up to four image outputs simultaneously in a single batch, enabling exploration of differing creative directions.
• Reference and Multi-Image Composition: The model supports up to 14 reference images as context, allowing for advanced multi-image compositions or guided creative outputs.
• Character Consistency: When editing groups of people, Nano Banana Pro maintains recognizable character attributes for up to five individuals across generated images, preserving likeness and details over multiple edits.
• Composition-Aware Transforms: Edits respect and maintain depth, perspective, and lighting effects without manual intervention — shadows, highlights, and reflections adjust correctly according to changes.
• Enhanced Text Rendering: Notably, the model includes advanced capabilities for rendering text and sustaining character detail, a strength compared to prior generations and many peer models.

Intended Use Cases and Users Documented workflows for Nano Banana Pro include:

• Product iteration for creative teams
• Refinement of creative assets
• Context-aware professional photo editing
• Construction of complex, multi-image compositions

It is designed for professional and commercial-use scenarios where high quality, semantic accuracy, and efficient creative iteration are critical.

Technical Specifications

• Input Modalities: The model accepts both image URLs (required) and text prompts (required). Drag-and-drop, clipboard pasting, or URL provision are supported for image inputs.
• Output Modalities: Outputs are provided as images (PNG, JPEG, or WebP, user-selectable) with optional JSON metadata.
• Resolution Options: 1K (1024px), 2K (2048px), and 4K (higher output size), configurable via API. Higher resolutions are available, allowing for professional asset creation.
• Aspect Ratio Support: The system supports a broad range of aspect ratios, including auto, 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, and 9:16, providing flexibility for varied creative needs.
• Batch Size: Process between 1 and 4 images per request.
• Multi-Image Support: Compose scenes with up to 14 input images for advanced creative effects or reference-based editing.
• Required Fields: Each inference requires both a prompt (natural language description of edits) and one or more image URLs.
• Digital Watermarking: All outputs include SynthID digital watermarking by default.
• Commercial Licensing: Outputs are suitable for commercial applications under the provided license terms.

Quality and Performance Built on Google’s Gemini 3 Pro architecture, Nano Banana Pro prioritizes output quality, compositional reasoning, and semantic understanding, sometimes at the expense of speed. The model is especially well-suited for intricate editing instructions and professional creative control, with a generation philosophy that favors precision and thoughtful composition over fast turnarounds. Performance benchmarks such as speed are not disclosed; the focus is on reasoning-driven image manipulation and professional output fidelity.

Model Configuration The following configurable parameters are available:

• Aspect ratio (from a pre-set list)
• Enable/disable web search for generation
• Resolution selection
• Number of images to generate per request
• Output file format (PNG, JPEG, WebP)
• Synchronous vs. asynchronous output handling
• Generations can be limited to one per round using an optional experimental parameter

Limitations and Best Practices

• High-resolution outputs (2K/4K) may increase inference time and computational load.
• Manual masking or traditional layer-based editing is not supported; all edits are achieved via semantic and context-aware natural language prompts.
• The model supports up to five consistent characters (people) across edits and up to fourteen reference images in a single composition.
• Watermarking is applied to all generated images.
• Generation time is not public but may be slower than simpler or less capable models due to its quality-first design.

Comparison to Prior and Peer Models Compared with its predecessor (Nano Banana/Gemini 2.5 Flash Image), Nano Banana Pro offers significantly improved semantic reasoning, professional text rendering, character consistency, and multi-image composition for more advanced editing applications. Where the earlier version excelled at rapid iteration and simple edits, Nano Banana Pro is tailored for complex, quality-driven creative requirements.

Its differentiators from other models include context-aware editing without manual masking, precise text and character handling, and the ability to combine up to fourteen images per composition.

Summary Nano Banana Pro brings production-scale, context-sensitive image editing and generation to creative and commercial workflows. By interpreting natural language instructions with advanced understanding of compositional relationships, it delivers quality-first professional assets without reliance on labor-intensive manual techniques.