image-generation

name	image-generation
description	Generate and edit images with the Gemini API. Use when the user asks for text-to-image, image editing, aspect-ratio/resolution controls, or image prompt refinement.

Gemini Image Generation

When to use this skill

Use this skill when the user wants to:

• Generate new images from text prompts
• Edit an existing image with natural language instructions
• Choose the right Gemini image model for quality/speed tradeoffs
• Control aspect ratio or output resolution
• Improve output quality through better prompting

Requirements

• GEMINI_API_KEY available in your environment
• uv installed

Quickstart (minimal examples)

Text-to-image

uv run --with google-genai --with pillow python - <<'PY'
from google import genai
from PIL import Image

client = genai.Client()

prompt = "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme"
response = client.models.generate_content(
    model="gemini-3.1-flash-image-preview",
    contents=[prompt],
)

for part in response.parts:
    if part.text is not None:
        print(part.text)
    elif part.inline_data is not None:
        image = part.as_image()
        image.save("generated_image.png")
PY

Image editing (prompt + input image)

uv run --with google-genai --with pillow python - <<'PY'
from google import genai
from google.genai import types
from PIL import Image

client = genai.Client()

prompt = (
    "Create a picture of my cat eating a nano-banana in a "
    "fancy restaurant under the Gemini constellation"
)

image = Image.open("/path/to/cat_image.png")

response = client.models.generate_content(
    model="gemini-3.1-flash-image-preview",
    contents=[prompt, image],
)

for part in response.parts:
    if part.text is not None:
        print(part.text)
    elif part.inline_data is not None:
        output_image = part.as_image()
        output_image.save("generated_image.png")
PY

Model selection guideline

• Gemini 3.1 Flash Image Preview (Nano Banana 2 Preview)

  • Default choice for most tasks
  • Best overall quality/intelligence/cost/latency balance

• Gemini 3 Pro Image Preview (Nano Banana Pro Preview)

  • Professional asset production and complex instructions
  • Google Search grounding + default thinking behavior
  • Up to 4K output

• Gemini 2.5 Flash Image (Nano Banana)

  • Speed-first and high-volume workloads
  • Low latency, typically 1024px-class output

Aspect ratio and resolution

Default behavior:

• With an input image: output usually follows input dimensions
• Without input image: output defaults to 1:1

Use image_config.aspect_ratio for framing and image_config.image_size (3.1/3 Pro) for resolution tier.

from google.genai import types

# gemini-2.5-flash-image
response = client.models.generate_content(
    model="gemini-2.5-flash-image",
    contents=[prompt],
    config=types.GenerateContentConfig(
        image_config=types.ImageConfig(
            aspect_ratio="16:9",
        )
    ),
)

# gemini-3.1-flash-image-preview and gemini-3-pro-image-preview
response = client.models.generate_content(
    model="gemini-3.1-flash-image-preview",
    contents=[prompt],
    config=types.GenerateContentConfig(
        image_config=types.ImageConfig(
            aspect_ratio="16:9",
            image_size="2K",
        )
    ),
)

Resolution guidance

• 1K: drafts and fast iteration
• 2K: standard production default
• 4K: high-detail deliverables
• Higher resolution increases latency, token usage, and memory usage

Common aspect ratios

• 1:1 — social posts, thumbnails, avatars
• 16:9 — slides, YouTube, landscape banners
• 9:16 — stories, reels, shorts
• 4:5 — social feed posts
• 3:2 or 4:3 — photography-style framing

Prompting strategies (good → great)

• Be hyper-specific: add concrete details, not vague labels.
• Provide context and intent: include the image purpose (brand ad, concept art, product mockup, etc.).
• Iterate and refine: do follow-up edits instead of restarting from scratch.
• Use step-by-step instructions: especially for complex multi-object scenes.
• Use semantic negative prompts: describe desired absence positively (for example, "an empty street with no traffic").
• Control the camera: use terms like "wide-angle shot", "macro shot", and "low-angle perspective".

Output handling

• Responses may include both text and image parts
• Save image parts from part.inline_data with part.as_image()
• If no image is returned, refine prompt and retry