Nano Banana 2 Lite API Cost Guide (2026): Pricing, Setup & Routing

On June 30, 2026, Google released Nano Banana 2 Lite to developers through Google AI Studio, the Gemini API, and Gemini Enterprise Agent Platform. The important part for API builders is not the cute name. It is the price: Google lists gemini-3.1-flash-lite-image at $0.25 per million input tokens and $30 per million image output tokens, which works out to $0.0336 for a 1K image.

That changes how you should build image workflows. Instead of sending every prompt to a premium image model, you can use Nano Banana 2 Lite as the fast draft layer, escalate only the winners to Nano Banana 2 or Gemini 3 Pro Image, and keep your product experience responsive.

Confirmed Pricing

Here is the practical pricing table developers should put in budget spreadsheets. Prices are from Google's Gemini API pricing page as checked on July 6, 2026.

Model Comparison: Which Banana Should You Pick?

The Routing Pattern I’d Use in Production

The mistake is treating image generation like one model should handle everything. Text teams learned this lesson with LLM routing years ago. Image generation needs the same pattern.

1. Draft on Lite. Generate 4–8 candidates cheaply with gemini-3.1-flash-lite-image.
2. Score automatically. Use a text or vision model to reject images with bad text, broken composition, or policy issues.
3. Escalate only winners. Send the best prompt or reference image to Nano Banana 2 or Nano Banana Pro.
4. Cache prompt ingredients. Store brand style, negative examples, and approved prompt templates so every run is reproducible.

For teams already using an OpenAI-compatible gateway, KissAPI can sit next to your native Gemini integration as the fallback layer for text reasoning, prompt rewriting, and routing decisions. Keep the image call native where needed, but don't hardwire the whole workflow to one provider.

Minimal curl Example

Google's SDKs are the easiest path, but the structure below shows the core idea: model ID, prompt, and image output request.

curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [{
        "text": "Create a clean 1K product mockup of a developer dashboard showing API cost savings. Dark background, purple accent, no logos."
      }]
    }],
    "generationConfig": {
      "responseModalities": ["IMAGE"]
    }
  }'

Python: Batch Drafts Before Escalation

from google import genai

client = genai.Client(api_key="YOUR_GEMINI_API_KEY")

PROMPTS = [
    "Dark SaaS dashboard hero image, purple accent, no text.",
    "Developer API cost chart, clean UI, 1K square image.",
    "Minimal product mockup showing token savings, dark theme."
]

for i, prompt in enumerate(PROMPTS):
    result = client.models.generate_content(
        model="gemini-3.1-flash-lite-image",
        contents=prompt,
        config={"response_modalities": ["IMAGE"]}
    )
    # Save image parts from result according to the SDK response shape.
    print(f"draft {i}: generated")

In a real pipeline, the next step is not “send everything to Pro.” First run a cheap quality gate: does the image contain readable text, is the subject centered, did it ignore the style constraints, and is the aspect ratio correct?

Node.js: Add a Simple Cost Guard

const MAX_DRAFTS_PER_USER = 12;
const LITE_1K_IMAGE_USD = 0.0336;

function estimateDraftCost(count) {
  return count * LITE_1K_IMAGE_USD;
}

async function createDrafts({ userId, prompts }) {
  if (prompts.length > MAX_DRAFTS_PER_USER) {
    throw new Error("Too many draft images in one request");
  }

  const estimated = estimateDraftCost(prompts.length);
  console.log(`estimated Nano Banana 2 Lite cost: $${estimated.toFixed(4)}`);

  // Call the Gemini API with model: gemini-3.1-flash-lite-image
  // Then score and escalate only the strongest outputs.
}

Budget Math: Why Lite Is the Draft Layer

If a user asks for eight 1K draft images, Nano Banana 2 Lite costs about $0.2688. The same eight images on Nano Banana 2 cost about $0.536. On Nano Banana Pro at $0.134 per 1K/2K image, the same draft burst costs about $1.072.

That difference looks small for one user. It becomes ugly at 10,000 users. For high-volume apps, the right architecture is obvious: Lite for exploration, Pro for finalization.

When Not to Use Nano Banana 2 Lite

Don't use Lite when the image is the product and mistakes are expensive. Brand campaigns, ad creatives with exact text, regulated diagrams, medical-style visuals, or high-stakes product renders deserve a stronger model and human review.

Do use it when the point is iteration. Product teams, ecommerce sellers, game asset prototypers, and social content tools can all benefit from a cheap visual sketchpad.

FAQ

What is Nano Banana 2 Lite?

Nano Banana 2 Lite is Google's low-latency, low-cost Gemini image model for fast image generation and editing. It is exposed through the Gemini API as gemini-3.1-flash-lite-image.

How much does a 1K Nano Banana 2 Lite image cost?

A standard 1K 1024x1024 output image costs $0.0336 because Google prices image output at $30 per million tokens and a 1K image consumes 1,120 output tokens.

Is Nano Banana 2 Lite better than Nano Banana Pro?

No. It is cheaper and faster, not universally better. Nano Banana 2 Lite is the better draft model. Nano Banana Pro is the better final-image model when accuracy, control, and quality matter more than cost.