Nano Banana Pro (gemini-3-pro-image) Model Card #
Overview #
Nano Banana Pro (gemini-3-pro-image) is Google’s state-of-the-art visual foundation model designed for professional studio asset production, complex multi-reference character and style consistency, high-precision typography rendering, and interleaved multi-image narrative composition.
- Model Code:
gemini-3-pro-image - Release Date: November 2025
- Status: General Availability (GA)
- DeepMind Model Card: gemini-3-pro-image
Technical Specifications #
| Property | Value |
|---|---|
| Input Modalities | Text, Images (up to 14), PDF |
| Output Modalities | Image and Text (Interleaved) |
| Input Token Limit | 65,536 tokens |
| Output Token Limit | 32,768 tokens |
| Supported Resolutions | 1K (1024px), 2K (2048px), 4K (4096px) |
| Aspect Ratios | 10 standard professional ratios |
| Thinking Mode | Enabled by Default (deep visual reasoning prior to synthesis) |
| Search Grounding | Web Search Grounding supported |
| Multi-Reference Anchors | Up to 14 total: up to 6 objects + up to 5 characters + up to 3 style references |
| Interleaved Output | Supported (multi-scene storyboard / illustrated narrative) |
| Watermarking | SynthID (Always On) + C2PA Metadata |
Resolution Grid & Token Consumption #
| Aspect Ratio | 1K Resolution | 1K Tokens | 2K Resolution | 2K Tokens | 4K Resolution | 4K Tokens |
|---|---|---|---|---|---|---|
1:1 | 1024 × 1024 | 1,120 | 2048 × 2048 | 1,120 | 4096 × 4096 | 2,000 |
2:3 | 848 × 1264 | 1,120 | 1696 × 2528 | 1,120 | 3392 × 5056 | 2,000 |
3:2 | 1264 × 848 | 1,120 | 2528 × 1696 | 1,120 | 5056 × 3392 | 2,000 |
3:4 | 896 × 1200 | 1,120 | 1792 × 2400 | 1,120 | 3584 × 4800 | 2,000 |
4:3 | 1200 × 896 | 1,120 | 2400 × 1792 | 1,120 | 4800 × 3584 | 2,000 |
4:5 | 928 × 1152 | 1,120 | 1856 × 2304 | 1,120 | 3712 × 4608 | 2,000 |
5:4 | 1152 × 928 | 1,120 | 2304 × 1856 | 1,120 | 4608 × 3712 | 2,000 |
9:16 | 768 × 1376 | 1,120 | 1536 × 2752 | 1,120 | 3072 × 5504 | 2,000 |
16:9 | 1376 × 768 | 1,120 | 2752 × 1536 | 1,120 | 5504 × 3072 | 2,000 |
21:9 | 1584 × 672 | 1,120 | 3168 × 1344 | 1,120 | 6336 × 2688 | 2,000 |
Capabilities & Key Features #
1. Multi-Reference Character & Style Consistency #
Nano Banana Pro excels at maintaining exact facial, anatomical, and wardrobe consistency across varied poses, while simultaneously adhering to an artistic style defined by separate reference images:
- Object Anchors (up to 6): Maintain exact physical proportions and logo placements.
- Character Anchors (up to 5): Preserve identity across 360-degree viewpoints and emotional expressions.
- Style References (up to 3): Match custom painterly or graphic art styles.
2. Built-in Visual Thinking Reasoning #
Nano Banana Pro runs pre-generation reasoning cycles that evaluate composition, lighting angles, focal depth, and spatial consistency before emitting pixels.
3. Interleaved Storyboard & Multi-Image Generation #
Can produce multi-panel graphic novels, children’s book spreads, or technical step-by-step illustrations with matching text in a single generation call.
SDK Code Examples #
1. Studio-Quality 4K Asset Production with Search Grounding #
python
import base64
from google import genai
client = genai.Client()
interaction = client.interactions.create(
model="gemini-3-pro-image",
input="An authentic photographic architectural render of the newly constructed Grand Egyptian Museum at sunset, with precise structural accuracy.",
tools=[{"type": "google_search"}],
response_format={
"type": "image",
"aspect_ratio": "16:9",
"image_size": "4K",
},
)
if interaction.output_image:
with open("gem_museum_4k.png", "wb") as f:
f.write(base64.b64decode(interaction.output_image.data))2. Multi-Reference Style & Character Consistency #
python
import base64
from google import genai
client = genai.Client()
def read_b64(path):
with open(path, "rb") as f:
return base64.b64encode(f.read()).decode("utf-8")
interaction = client.interactions.create(
model="gemini-3-pro-image",
input=[
{"type": "image", "data": read_b64("references/character_face.png"), "mime_type": "image/png"},
{"type": "image", "data": read_b64("references/character_body.png"), "mime_type": "image/png"},
{"type": "image", "data": read_b64("references/art_style.png"), "mime_type": "image/png"},
{
"type": "text",
"text": "Render the character from images 1 and 2 wearing a leather flight jacket and aviator goggles, standing beside a vintage plane. Recreate the entire scene in the exact watercolor and ink style of image 3.",
},
],
response_format={"type": "image", "aspect_ratio": "3:2", "image_size": "2K"},
)
if interaction.output_image:
with open("character_rendered.png", "wb") as f:
f.write(base64.b64decode(interaction.output_image.data))