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AI / Google Antigravity Gemini Fundamentals Interview Questions

What are the Nano Banana image generation models and how do they replace Imagen?

Nano Banana is Google's branding for the Gemini native image generation models. They replace the older Imagen models (deprecated, shut down by June 30, 2026) and are natively integrated into the Gemini model family rather than being a separate product.

Nano Banana model lineup
ModelAlso known asStrength
Gemini 3 Pro ImageNano Banana ProHighest quality; reasoning-enhanced composition; legible text; complex multi-turn editing; up to 14 reference inputs
Gemini 3.1 Flash ImageNano Banana 2High-efficiency, high-volume; multi-image fusion; character consistency
Gemini 3.1 Flash-Lite ImageNano Banana 2 LiteUltra-low latency; cost-effective; for high-volume and latency-sensitive workloads
from google import genai

client = genai.Client()

# Generate an image with Nano Banana 2 (Gemini 3.1 Flash Image)
interaction = client.interactions.create(
    model="gemini-3.1-flash-image-preview",  # Nano Banana 2
    input="A photorealistic image of a Python snake debugging code on a glowing terminal.",
)
# Access the generated image:
for step in interaction.steps:
    if step.type == "model_output":
        for part in step.content:
            if part.type == "image":
                with open("output.png", "wb") as f:
                    f.write(part.data)  # image bytes

# Multi-turn editing (conversational editing):
edit = client.interactions.create(
    model="gemini-3.1-flash-image-preview",
    input="Now make the snake wearing a debugging hat and smiling.",
    previous_interaction_id=interaction.id,  # maintains image context
)

# Or via generateContent with Gen Media endpoint:
response = client.models.generate_images(
    model="gemini-3-pro-image-preview",   # Nano Banana Pro
    prompt="Studio quality portrait of an AI robot",
)

What are the Nano Banana models replacing in the Gemini API ecosystem?
What distinguishes Nano Banana Pro (Gemini 3 Pro Image) from Nano Banana 2 Lite?

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