How to Generate 4K Images with Nano Banana: App, API, and Wrapper Routes

To generate real 4K with Nano Banana, choose the surface first. For exact size control, use AI Studio, the Gemini API, or Vertex AI with a Gemini 3 image model and set imageSize: "4K" in image config; use Nano Banana 2 as the efficient default and Nano Banana Pro only when the asset needs stronger text, grounding, diagrams, or final-production polish.

The short answer: start with gemini-3.1-flash-image-preview (Nano Banana 2) for most 4K API work, switch to gemini-3-pro-image-preview (Nano Banana Pro) when the output must handle difficult text, diagrams, grounded details, or client-facing final polish, and stop using the older Pro-only rule. Prompting "4K quality" is not the same as setting the API output size.

Which Nano Banana Route Should You Use?

The confusing part is that "Nano Banana" no longer points to one simple product contract. It can mean the Gemini app experience, Flow, Google AI Studio, the Gemini API, Vertex AI, the newer Nano Banana 2 model, the higher-end Nano Banana Pro model, the older Nano Banana model, or a third-party page that uses the name in its own product interface. The right route depends on how much control you need.

If you just want to create an image quickly, the Gemini app or Flow can be the fastest route. They are product surfaces, not a promise that every download path exposes the same exact pixel dimensions as the API. Use them when you value speed, iteration, and built-in product UX more than programmatic control.

If you need exact 4K behavior, use AI Studio, the Gemini API, or Vertex AI. Those surfaces let you choose the model and set the image-size field. That is the route for developers building image products, marketing pipelines, asset-generation tools, or automated creative workflows.

If a third-party wrapper promises "free Nano Banana 4K," treat that as a separate provider contract. It may be useful, but its credits, resolution labels, model routing, output verification, and upscaling behavior are not Google official API pricing or entitlement. A wrapper can be a valid shortcut when setup friction matters; it should not be your source of truth for model IDs, dimensions, or official prices.

The Current Model Map: Nano Banana 2, Pro, and Original Nano Banana

Google's current Gemini API image-generation docs separate the family this way:

That model map changes the old advice. Nano Banana Pro is no longer the only model you should associate with 4K. It is the premium route. For many API jobs, Nano Banana 2 is the better first try because it supports 4K while staying closer to the cost and latency profile a production workflow usually wants.

Choose Nano Banana 2 first when you need a high-resolution product mockup, social creative, marketplace image, editorial visual, or fast iteration that still needs 4K output. Move to Nano Banana Pro when the image has dense text, small labels, diagram structure, brand-sensitive typography, grounded factual details, or a final-asset review bar where a cheaper result would create manual cleanup.

The API Setting That Actually Requests 4K

The API size is controlled by image config, not by the prompt alone. You can ask for "4K quality" in the prompt to describe style and detail, but the output size comes from imageSize or image_size depending on the SDK surface.

For JavaScript-style configuration, the important field is imageConfig.imageSize:

hljs jsCopy
const result = await ai.models.generateContent({
  model: "gemini-3.1-flash-image-preview",
  contents: [{ role: "user", parts: [{ text: prompt }] }],
  config: {
    responseModalities: ["IMAGE"],
    imageConfig: {
      imageSize: "4K",
      aspectRatio: "16:9",
    },
  },
});

For Python-style configuration, the same idea appears as image_config.image_size:

hljs pythonCopy
response = client.models.generate_content(
    model="gemini-3.1-flash-image-preview",
    contents=prompt,
    config={
        "response_modalities": ["IMAGE"],
        "image_config": {
            "image_size": "4K",
            "aspect_ratio": "16:9",
        },
    },
)

Use gemini-3-pro-image-preview in the same pattern when the job justifies Nano Banana Pro. The size field stays the important control. If the output remains 1K or 2K, check the model and image config before rewriting the prompt.

4K Dimensions and Official Price Boundary

As checked on April 25, 2026, Google's Gemini API docs list 4K outputs for Gemini 3.1 Flash Image Preview and Gemini 3 Pro Image Preview. Common 4K dimensions include:

The pricing boundary matters because many wrappers advertise "free 4K" as their own product promise. Google's official API rows checked on April 25, 2026 show 4K image output as a paid API contract:

Batch or Flex rows may change the cost, and search grounding charges are separate. Do not collapse those into one timeless price. For a production quote, re-check the official pricing page and record the date.

Should You Use 2K, 4K, or Pro?

4K is not always the best first setting. It is useful when the image will be cropped, printed, shown on large screens, used as a hero asset, handed to a client, or reused across multiple layouts. It is also useful when downstream compression will reduce visible detail and you want more source pixels.

Use 2K when the asset is for a web card, a draft, an internal review, or a concept board where cost and iteration speed matter more than final resolution. Generate multiple 2K candidates, choose the strongest composition, then regenerate the final prompt at 4K if the workflow supports it.

Use Nano Banana Pro only when quality risk is higher than cost. Text-heavy posters, UI mockups, infographics, packaging, grounded product scenes, diagrams, and brand-sensitive images often justify Pro. A simple lifestyle image, background, or first-pass creative variation often does not.

The practical default is:

Why Your Image Stayed at 1K or 2K

If the result is still low resolution, do not start by adding more adjectives to the prompt. First check the route.

Wrong model. If you used the original gemini-2.5-flash-image, you are in the older 1024px-class route. Use gemini-3.1-flash-image-preview or gemini-3-pro-image-preview for current 4K API work.

Missing image config. If your code only says "make it 4K" in the prompt, the model may improve perceived detail without changing the output size. Set imageSize: "4K" or image_size="4K" in image config.

Consumer surface limit. If you are using the Gemini app or Flow, the UI, account tier, region, project settings, or export path may decide what file you can download. Check the product surface rather than assuming the API table applies directly.

Wrapper upscaling. A third-party tool may route through a model, upscale after generation, compress on download, or expose a different "quality" control. Read the provider docs and verify the actual file properties after download.

Aspect ratio mismatch. If you ask for a format that is not supported by the surface, the provider may fall back to a default size. Keep aspect ratio and size settings explicit.

Quota or billing boundary. If a route requires billing or a paid plan for higher resolution, the system may silently limit output or return an error. Treat plan and quota checks as part of resolution troubleshooting.

Prompting for Better 4K Results

After the route and size are correct, prompt quality still matters. A good 4K prompt should tell the model what the image is, what details must stay sharp, what composition should dominate, and what must be avoided.

For a product-style image:

hljs textCopy
Create a 4K hero image of a matte black smart desk lamp on a walnut table,
soft morning window light, clean background, accurate product geometry,
sharp edge detail, no visible brand logos, no extra objects.

For an information-heavy asset:

hljs textCopy
Create a clean technical information board about Nano Banana 4K routing,
large readable labels, grouped panels, teal and graphite palette,
icons for app, API, cloud, and wrapper routes, no tiny text, no fake UI.

For a final asset, keep the prompt shorter than your design brief but more specific than a mood phrase. The model should know the subject, composition, required details, style, constraints, and what would make the output unusable.

The Safe Workflow for Production 4K

For repeatable production, use a three-pass workflow:

1. Generate several 1K or 2K candidates with Nano Banana 2 to explore composition.
2. Lock the strongest prompt, aspect ratio, and negative constraints.
3. Regenerate the final candidate at 4K with Nano Banana 2, or switch to Nano Banana Pro if text, diagrams, grounding, or final polish are the risk.

Then verify the result. Open file properties, check image dimensions, inspect compression artifacts, and confirm that the output matches the intended downstream use. For automated systems, store the model ID, size setting, aspect ratio, prompt version, and output dimensions with the asset record so later failures are debuggable.

FAQ

Which current models support 4K output?

Yes, the current Gemini 3 image routes support 4K through Nano Banana 2 (gemini-3.1-flash-image-preview) and Nano Banana Pro (gemini-3-pro-image-preview). The older original Nano Banana model is not the current 4K API route.

Which API parameter controls output size?

Use the image config size field: imageSize: "4K" in JavaScript/REST-style configuration or image_size="4K" in Python-style configuration. Prompt wording alone is not enough.

Is official API 4K output free?

Official Gemini API 4K image output is paid in the rows checked on April 25, 2026. Consumer app behavior, Flow credits, and third-party wrapper "free" claims are separate contracts and should be verified on their own surfaces.

When should Pro replace Nano Banana 2?

Start with Nano Banana 2 for most API 4K work. Use Nano Banana Pro when the output needs stronger text rendering, diagrams, grounded details, complex instructions, or final-production polish.

Why did my output stay 1K or 2K?

The usual causes are the wrong model, missing image config, a consumer-surface export limit, unsupported aspect ratio, plan or billing limits, or a wrapper that upscales or compresses output. Check those before rewriting the prompt.

Are third-party wrapper generators safe to use?

They can be useful for quick tests, but treat them as separate providers. Verify their model routing, pricing, credits, output dimensions, privacy terms, and whether "4K" means native generation or post-generation upscaling.