Nano Banana 2

AI Image Editing Model

Image Featured #1 #2 $$ · 2.2¢

Gemini 3.1 Flash with image generation capabilities. High-efficiency image generation model with support for text rendering, reference images, search grounding, and thinking mode. The efficient counterpart to Gemini 3 Pro Image.

Nano Banana 2 generated image of A cinematic wide shot of an ornate, sun-drenched European conservatory librar...
Nano Banana 2 generated image of Cinematic wide shot of a master carpenter's sun-drenched workshop, dust motes...
1.0M
Context Window
Supported Modes
Text to Image Image Edit
Active

Capabilities

Function calling Structured output Batch Streaming System prompt Tool use Grounding Thinking Code execution Json mode

Details

Model ID
gemini-3.1-flash-image-preview
Also known as: gemini-3.1-flash-image
Creator
Family
gemini-3.1-flash
Released
February 2026
Max Input Images
14
Max Output Tokens
65,536
Tags
multimodal image-generation fast
// Get Started

Ready to integrate?

Access gemini-3.1-flash-image-preview via our unified API.

Create Account
Available at 4 providers

Starting from

$0.045 /image via Gemini API, Vertex AI · +2 more

Batch from $0.022/image via Gemini API, Vertex AI

Popular formats

0.5K (512×512)
~$0.050
2K (2048×2048)
~$0.106
4K (4096×4096)
~$0.153

Prices shown are in USD

See all providers

Provider Performance

Fastest generation through replicate at 15,218ms median latency with 86.9% success rate.

Aggregated from real API requests over the last 30 days.

Generation Time

replicate
15,218ms p95: 23,589ms
vertex
22,007ms p95: 58,852ms
gemini
22,456ms p95: 39,408ms
fal
61,416ms p95: 112,231ms

Success Rate

replicate
86.9%
53 / 61 requests
vertex
49.1%
230 / 468 requests
gemini
88.6%
1,845 / 2,083 requests
fal
83.7%
169 / 202 requests

Time to First Byte

replicate
15,218ms
p95: 23,244ms
gemini
19,152ms
p95: 33,301ms
vertex
21,111ms
p95: 58,518ms
fal
61,416ms
p95: 113,837ms

Provider Rankings

# Provider p50 Gen Time p95 Gen Time Success Rate TTFB (p50)
1 replicate 15,218ms 23,589ms 86.9% 15,218ms
2 vertex 22,007ms 58,852ms 49.1% 21,111ms
3 gemini 22,456ms 39,408ms 88.6% 19,152ms
4 fal 61,416ms 112,231ms 83.7% 61,416ms
Data updated every 15 minutes. Based on all API requests through Lumenfall over the last 30 days.

Providers & Pricing (5)

Nano Banana 2 is available from 5 providers, with per-image pricing starting at $0.0225 through fal.ai.

fal.ai
Text to Image
fal/gemini-3.1-flash-image-preview
Provider Model ID: fal-ai/nano-banana-2

Output

Image 0.5K
$0.060 per image
Image 1K
$0.080 per image
Image 2K
$0.120 per image
Image 4K
$0.160 per image
Pricing Notes (5)
  • $0.08 per image at 1K (standard rate)
  • 0.5K outputs charged at 0.75x ($0.06)
  • 2K outputs charged at 1.5x ($0.12)
  • 4K outputs charged at 2x ($0.16)
  • Web search adds $0.015 per request
View official pricing • As of
fal.ai
Image Edit
fal/gemini-3.1-flash-image-preview-edit
Provider Model ID: fal-ai/nano-banana-2/edit

Output

Image 0.5K
$0.060 per image
Image 1K
$0.080 per image
Image 2K
$0.120 per image
Image 4K
$0.160 per image
Pricing Notes (5)
  • $0.08 per image at 1K (standard rate)
  • 0.5K outputs charged at 0.75x ($0.06)
  • 2K outputs charged at 1.5x ($0.12)
  • 4K outputs charged at 2x ($0.16)
  • Web search adds $0.015 per request
View official pricing • As of
Replicate
Text to Image Image Edit
replicate/gemini-3.1-flash-image-preview
Provider Model ID: google/nano-banana-2

Output

Image 1K
$0.067 per image
Image 2K
$0.101 per image
Image 4K
$0.151 per image
Pricing Notes (3)
  • $0.067 per output image at 1K
  • $0.101 per output image at 2K
  • $0.151 per output image at 4K
View official pricing • As of
Gemini API
Text to Image Image Edit
gemini/gemini-3.1-flash-image-preview
Provider Model ID: gemini-3.1-flash-image-preview

Input

Token
$0.250 per 1M or $0.125 batched

Output

Token text
$1.50 per 1M or $0.125 batched
Image 0.5K
$0.045 per image or $0.022 batched
Image 1K
$0.067 per image or $0.034 batched
Image 2K
$0.101 per image or $0.050 batched
Image 4K
$0.151 per image or $0.076 batched
Pricing Notes (4)
  • $0.045 per output image at 512px (0.5K) (747 tokens)
  • $0.067 per output image at 1024x1024px (1K) (1120 tokens)
  • $0.101 per output image at 2048x2048px (2K) (1680 tokens)
  • $0.151 per output image at 4096x4096px (4K) (2520 tokens)
View official pricing • As of
Vertex AI
Text to Image Image Edit
vertex/gemini-3.1-flash-image-preview
Provider Model ID: gemini-3.1-flash-image-preview

Input

Token
$0.250 per 1M or $0.125 batched

Output

Token text
$1.50 per 1M or $0.125 batched
Image 0.5K
$0.045 per image or $0.022 batched
Image 1K
$0.067 per image or $0.034 batched
Image 2K
$0.101 per image or $0.050 batched
Image 4K
$0.151 per image or $0.076 batched
Pricing Notes (4)
  • $0.045 per output image at 512px (0.5K) (747 tokens)
  • $0.067 per output image at 1024x1024px (1K) (1120 tokens)
  • $0.101 per output image at 2048x2048px (2K) (1680 tokens)
  • $0.151 per output image at 4096x4096px (4K) (2520 tokens)
View official pricing • As of

gemini-3.1-flash-image API OpenAI-compatible

Connect to Nano Banana 2 via the Lumenfall OpenAI-compatible API to integrate high-speed text-to-image generation and image editing into your workflow. The unified endpoint allows for programmatic creation of visual assets and precise modifications to existing images through a single interface.

Base URL
https://api.lumenfall.ai/openai/v1
Model
gemini-3.1-flash-image-preview

Code Examples

Text to Image

/v1/images/generations
curl -X POST \
  https://api.lumenfall.ai/openai/v1/images/generations \
  -H "Authorization: Bearer $LUMENFALL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.1-flash-image-preview",
    "prompt": "",
    "size": "1024x1024"
  }'
# Response:
# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }

Image Edit

/v1/images/edits
curl -X POST \
  https://api.lumenfall.ai/openai/v1/images/edits \
  -H "Authorization: Bearer $LUMENFALL_API_KEY" \
  -F "model=gemini-3.1-flash-image-preview" \
  -F "[email protected]" \
  -F "prompt=Add a starry night sky to this image" \
  -F "size=1024x1024"
# Response:
# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }

Parameter Reference

Required Supported Not available

Core Parameters

Parameter Type Description Modes
prompt string Required. Text prompt for image generation
T2I Edit
seed integer Random seed for reproducibility
T2I Edit

Size & Layout

Parameter Type Description Modes
size string Image dimensions as WxH pixels (e.g. "1024x1024") or aspect ratio (e.g. "16:9")
WxH determines both shape and scale (aspect_ratio and resolution are ignored when size is provided). W:H format is equivalent to aspect_ratio.
T2I Edit
aspect_ratio string Aspect ratio of the output image (e.g. "16:9", "1:1")
Controls shape independently of scale. Use with resolution to control both. If size is also provided, size takes precedence. Any ratio is accepted and mapped to the nearest supported value.
T2I Edit
resolution string Output resolution tier (e.g. "1K", "4K")
auto 0.5K 1K 2K 4K
Controls scale independently of shape. Higher tiers produce larger images and cost more. If size is also provided, size takes precedence for scale. Any tier is accepted and mapped to the nearest supported value.
T2I Edit
Output size aspect_ratio + resolution
Flexible
Auto "auto" Model chooses optimal dimensions
0.5K 14 sizes
Output size aspect_ratio + resolution
573 × 458 "573x458" or "5:4" + "0.5K"
384 × 683 "384x683" or "9:16" + "0.5K"
683 × 384 "683x384" or "16:9" + "0.5K"
256 × 1024 "256x1024" or "1:4" + "0.5K"
512 × 512 "512x512" or "1:1" + "0.5K"
1024 × 256 "1024x256" or "4:1" + "0.5K"
181 × 1448 "181x1448" or "1:8" + "0.5K"
1448 × 181 "1448x181" or "8:1" + "0.5K"
418 × 627 "418x627" or "2:3" + "0.5K"
627 × 418 "627x418" or "3:2" + "0.5K"
458 × 572 "458x572" or "4:5" + "0.5K"
782 × 335 "782x335" or "21:9" + "0.5K"
443 × 591 "443x591" or "3:4" + "0.5K"
591 × 443 "591x443" or "4:3" + "0.5K"
1K 14 sizes
Output size aspect_ratio + resolution
1183 × 887 "1183x887" or "4:3" + "1K"
916 × 1145 "916x1145" or "4:5" + "1K"
1145 × 916 "1145x916" or "5:4" + "1K"
512 × 2048 "512x2048" or "1:4" + "1K"
1024 × 1024 "1024x1024" or "1:1" + "1K"
2048 × 512 "2048x512" or "4:1" + "1K"
887 × 1182 "887x1182" or "3:4" + "1K"
362 × 2896 "362x2896" or "1:8" + "1K"
2896 × 362 "2896x362" or "8:1" + "1K"
836 × 1254 "836x1254" or "2:3" + "1K"
1254 × 836 "1254x836" or "3:2" + "1K"
768 × 1365 "768x1365" or "9:16" + "1K"
1365 × 768 "1365x768" or "16:9" + "1K"
1563 × 670 "1563x670" or "21:9" + "1K"
2K 14 sizes
Output size aspect_ratio + resolution
3129 × 1341 "3129x1341" or "21:9" + "2K"
1774 × 2365 "1774x2365" or "3:4" + "2K"
2365 × 1774 "2365x1774" or "4:3" + "2K"
1832 × 2290 "1832x2290" or "4:5" + "2K"
2290 × 1832 "2290x1832" or "5:4" + "2K"
1536 × 2731 "1536x2731" or "9:16" + "2K"
2731 × 1536 "2731x1536" or "16:9" + "2K"
1024 × 4096 "1024x4096" or "1:4" + "2K"
2048 × 2048 "2048x2048" or "1:1" + "2K"
4096 × 1024 "4096x1024" or "4:1" + "2K"
724 × 5793 "724x5793" or "1:8" + "2K"
5792 × 724 "5792x724" or "8:1" + "2K"
1672 × 2508 "1672x2508" or "2:3" + "2K"
2508 × 1672 "2508x1672" or "3:2" + "2K"
4K 14 sizes
Output size aspect_ratio + resolution
3548 × 4730 "3548x4730" or "3:4" + "4K"
3345 × 5017 "3345x5017" or "2:3" + "4K"
4580 × 3664 "4580x3664" or "5:4" + "4K"
2048 × 8192 "2048x8192" or "1:4" + "4K"
4096 × 4096 "4096x4096" or "1:1" + "4K"
8192 × 2048 "8192x2048" or "4:1" + "4K"
3072 × 5461 "3072x5461" or "9:16" + "4K"
5461 × 3072 "5461x3072" or "16:9" + "4K"
1448 × 11585 "1448x11585" or "1:8" + "4K"
4729 × 3547 "4729x3547" or "4:3" + "4K"
11584 × 1448 "11584x1448" or "8:1" + "4K"
5016 × 3344 "5016x3344" or "3:2" + "4K"
3663 × 4579 "3663x4579" or "4:5" + "4K"
6256 × 2681 "6256x2681" or "21:9" + "4K"

How these parameters work

size

Exact pixel dimensions

"1920x1080"
aspect_ratio

Shape only, default scale

"16:9"
resolution

Scale tier, preserves shape

"1K"

Priority when combined

size aspect_ratio + resolution aspect_ratio resolution

size is most specific and always wins. aspect_ratio and resolution control shape and scale independently.

How matching works

Shape matching – we pick the closest supported ratio. Ask for 7:1 on a model with 4:1 and 8:1, you get 8:1.
Scale matching – providers use different tier formats: K tiers (0.5K 1K 2K 4K) or megapixel tiers (0.25 1). If the exact tier isn't available, you get the nearest one.
Dimension clamping – if a model has pixel limits, we clamp dimensions to fit and keep the aspect ratio intact.

Media Inputs

Parameter Type Description Modes
image file Required. Input image(s) to edit
Supports PNG, JPEG, WebP.
Up to 14 images per request.
T2I Edit

Output & Format

Parameter Type Description Modes
response_format string How to return the image
url b64_json
Default: "url"
T2I Edit
output_format string Output image format
png jpeg gif webp avif
Gateway converts to requested format if provider doesn't support it natively.
T2I Edit
output_compression integer Compression level for lossy formats (JPEG, WebP, AVIF)
T2I Edit
n integer Number of images to generate
Default: 1
Gateway generates multiple images in parallel even if provider only supports 1.
T2I Edit

Additional Parameters

Provider-specific passthrough fields, available only when the request is routed to the listed provider.

Parameter Type Description Modes
Universal
thinking string Model's internal reasoning effort (off, on, minimal, high)
high minimal off on
T2I Edit
fal
enable_web_search boolean Enable web search for the image generation task. This will allow the model to use the latest information from the web to generate the image.
T2I Edit
limit_generations boolean Experimental parameter to limit the number of generations from each round of prompting to 1. Set to `True` to to disregard any instructions in the prompt regarding the number of images to generate and ignore any intermediate images generated by the model. This may affect generation quality.
T2I Edit
safety_tolerance string The safety tolerance level for content moderation. 1 is the most strict (blocks most content), 6 is the least strict.
1 2 3 4 5 6
T2I Edit
sync_mode boolean If `True`, the media will be returned as a data URI and the output data won't be available in the request history.
T2I Edit
replicate
google_search boolean Use Google Web Search grounding to generate images based on real-time information (e.g. weather, sports scores, recent events).
T2I Edit
image_search boolean Use Google Image Search grounding to find web images as visual context for generation. When enabled, web search is also used automatically.
T2I Edit

Parameter Normalization

How we handle parameters across different providers

Not every provider speaks the same language. When you send a parameter, we handle it in one of four ways depending on what the model supports:

Behavior What happens Example
passthrough Sent as-is to the provider style, quality
renamed Same value, mapped to the field name the provider expects prompt
converted Transformed to the provider's native format size
emulated Works even if the provider has no concept of it n, response_format

Parameters we don't recognize pass straight through to the upstream API, so provider-specific options still work.

Nano Banana 2 Benchmarks

Nano Banana 2 (Gemini 3.1 Flash Image) ranks #1 in text-to-image generation with an Elo of 1302 and #6 in image editing with an Elo of 1223. This high-efficiency model demonstrates top-tier performance against competitors, maintaining competitive rankings across both creative and technical generation tasks.

Lumenfall Arena
#1
Text-to-Image
1287 Elo
Lumenfall Arena
#2
Image Editing
1238 Elo

Text-to-Image Landscape

1 model without pricing omitted

Elo vs Speed

24 models waiting for enough speed data

Image Editing Landscape

1 model without pricing omitted

Elo vs Speed

1 model waiting for enough speed data

Competition Results

Image Editing

Photorealism

View leaderboard
Image Editing
Source
Edit instruction

“Make a photo of the man driving the car down the California coastline”

Nano Banana 2 edited result for Bald man challenge
Original image before Nano Banana 2 editing
Before After
#3
Bald man challenge
15 models
Image Editing
Edit instruction

“Give the person a full, thick head of natural hair with realistic texture, density, and a natural hairline. Preserve facial features and lighting.”

Nano Banana 2 edited result for Neutral Expression to Genuine Smile
Original image before Nano Banana 2 editing
Before After
Image Editing
Edit instruction
{
  "action": "image_edit",
  "reference": "uploaded neutral portrait",
  "change": "Warm genuine Duchenne smile: lips curved up, slight natural teeth, soft eye crinkles, subtle cheek raise",
  "details": "Realistic smiling skin (dimples if present, soft cheek shadows), slightly brighter eyes; keep exact eye shape/color/iris",
  "preserve_exact": "Face identity/structure, eyes/nose/lips/eyebrows, hair, skin texture/pores/freckles, makeup, clothing, head pose, background, lighting, shadows, framing",
  "no_changes": "No face shape change, no new features, no gaze shift, no hair/clothing/lighting/background edits",
  "style": "Ultra-photorealistic 8K portrait, sharp face focus, natural soft lighting, realistic skin glow"
}
3 attempts – showing best result
Nano Banana 2 edited result for Night Sky Transformation
Original image before Nano Banana 2 editing
Before After
#11
Night Sky Transformation
16 models
Image Editing
Edit instruction

“Change the scene to night: a deep, dark sky with subtle, glistening stars visible behind the mountain.”

3 attempts – showing best result
Text-to-Image

Text Rendering

View leaderboard
#2
Vintage Cafe Logo
24 models
Text-to-Image
Prompt

“Vintage minimalist restaurant logo for "Caffè Florian", retro cloche dome with steam and "Est. 1720" banner, classic typography, warm brown and cream tones, subtle texture on light background, vector emblem style.”

#3
Modern Clean Menu
24 models
Text-to-Image
Prompt

“Modern minimalist restaurant menu design, white background with colorful food photos in grid, sections for appetizers/pizza/mains, bold sans-serif fonts, vibrant accents, clean professional layout for casual dining.”

Text-to-Image
Prompt

“Create a clean, modern vector infographic poster about the Apollo 11 mission. NASA-inspired palette (navy, white, muted red, light gray). Flat-vector style, crisp lines, consistent iconography, subtle gradients only. Steps (stop at landing): 1. Launch (Saturn Vicon) 2. Earth Orbit (Earth + orbit ring icon) 3. Translunar (trajectory arc icon) 4. Lunar Orbit (Moon + orbit ring icon) 5. Descent (lunar module descending icon) 6. Landing (lunar module on the surface icon) Small supporting elements (minimal text): • Crew strip: three silhouette icons with only last names: Armstrong, Aldrin, Collins. • Landing site marker: Moon pin labeled "Tranquility" only. Layout constraints: generous margins, large readable labels, clean background with subtle stars. Vector-only, print-poster look, high resolution.”

Prompt

“Ad for 'Magic Burger'. Dynamic, exploded burger with all components (bun, patty, cheese, lettuce, tomato, sauce) suspended in mid-air. Emphasize photorealistic detail and a sense of motion. Dark, fiery background with glowing embers. Integrate text: 'MAGIC BURGER' as a prominent title, 'LIMITED TIME ONLY' as a secondary message, and '€6.99' in a starburst, all rendered with a fiery, glowing effect.”

Image Editing

Anime

View leaderboard
Image Editing
Source
Edit instruction

“Transform this photo into a Studio Ghibli–inspired illustration. Use soft pastel colors, hand-painted textures, gentle lighting, dreamy backgrounds, and a warm, nostalgic mood”

Image Editing

Portrait

View leaderboard
Nano Banana 2 edited result for Bald man challenge
Original image before Nano Banana 2 editing
Before After
#3
Bald man challenge
15 models
Image Editing
Edit instruction

“Give the person a full, thick head of natural hair with realistic texture, density, and a natural hairline. Preserve facial features and lighting.”

Nano Banana 2 edited result for Neutral Expression to Genuine Smile
Original image before Nano Banana 2 editing
Before After
Image Editing
Edit instruction
{
  "action": "image_edit",
  "reference": "uploaded neutral portrait",
  "change": "Warm genuine Duchenne smile: lips curved up, slight natural teeth, soft eye crinkles, subtle cheek raise",
  "details": "Realistic smiling skin (dimples if present, soft cheek shadows), slightly brighter eyes; keep exact eye shape/color/iris",
  "preserve_exact": "Face identity/structure, eyes/nose/lips/eyebrows, hair, skin texture/pores/freckles, makeup, clothing, head pose, background, lighting, shadows, framing",
  "no_changes": "No face shape change, no new features, no gaze shift, no hair/clothing/lighting/background edits",
  "style": "Ultra-photorealistic 8K portrait, sharp face focus, natural soft lighting, realistic skin glow"
}
3 attempts – showing best result
Text-to-Image

Photorealism

View leaderboard
Text-to-Image
Prompt

“A candid street photo of an elderly Japanese man repairing a red bicycle in light rain, reflections on wet pavement, shallow depth of field, 50mm lens, natural skin texture, imperfect framing, motion blur from passing cars, cinematic but realistic, no stylization.”

Text-to-Image
Prompt

“Photorealistic scene inside a yellow New York taxi at night. A capybara is driving, wearing a yellow taxi driver cap and a dark jacket. It has a calm, professional expression and both front paws on the steering wheel. In the back seat sits a human businesswoman in a coat, looking at her phone with a completely normal, bored expression (as if this is just another normal ride). Through the windows you can see the streets of Manhattan at night with blurred lights. Realistic taxi interior, photorealistic, detailed fur and fabric, 35mm lens, night lighting with reflections, shallow depth of field.”

Prompt

“Ad for 'Magic Burger'. Dynamic, exploded burger with all components (bun, patty, cheese, lettuce, tomato, sauce) suspended in mid-air. Emphasize photorealistic detail and a sense of motion. Dark, fiery background with glowing embers. Integrate text: 'MAGIC BURGER' as a prominent title, 'LIMITED TIME ONLY' as a secondary message, and '€6.99' in a starburst, all rendered with a fiery, glowing effect.”

Text-to-Image

Product, Branding & Commercial

View leaderboard
#2
Vintage Cafe Logo
24 models
Text-to-Image
Prompt

“Vintage minimalist restaurant logo for "Caffè Florian", retro cloche dome with steam and "Est. 1720" banner, classic typography, warm brown and cream tones, subtle texture on light background, vector emblem style.”

Prompt

“Ad for 'Magic Burger'. Dynamic, exploded burger with all components (bun, patty, cheese, lettuce, tomato, sauce) suspended in mid-air. Emphasize photorealistic detail and a sense of motion. Dark, fiery background with glowing embers. Integrate text: 'MAGIC BURGER' as a prominent title, 'LIMITED TIME ONLY' as a secondary message, and '€6.99' in a starburst, all rendered with a fiery, glowing effect.”

Text-to-Image

Portrait

View leaderboard
#1
Fantasy Warrior
23 models
Text-to-Image
Prompt

“Close portrait of a battle-worn paladin in ornate engraved plate armor, hair braided with small beads, faint scars and dirt on the skin, warm torchlight reflecting off metal, shallow depth of field, bokeh sparks, lifelike eyes, highly detailed texture on leather straps and cloth underlayer.”

Uncategorized

Image Editing
Source
Edit instruction

“Create a caricature of me and my job. Make it exaggerated and humorous, incorporating my profession as a tv show anchor and my love for dogs and hockey.”

#3
Geometric Composition
26 models
Text-to-Image
Prompt

“A glass cube on a wooden table. Inside the cube is a small blue sphere. On top of the cube sits a red book. A green plant is behind the cube, partially visible through the glass. Soft window light from the left.”

Text-to-Image
Prompt

“Create a clear, 45° top-down isometric miniature 3D cartoon scene of Japan's signature dish: sushi, with soft refined textures, realistic PBR materials, gentle lighting, on a small raised diorama base with minimal garnish and plate. Solid light blue background. At top-center: 'JAPAN' in large bold text, 'SUSHI' below it, small flag icon. Perfectly centered, ultra-clean, high-clarity, square format.”

Text-to-Image
Prompt

“Hyper-photorealistic scene of fluffy baby animals—a golden retriever puppy, tabby kitten, baby bunny, and red fox kit—with big expressive eyes and ultra-detailed soft fur, playfully chasing butterflies and tumbling together in a lush wildflower meadow, warm golden sunrise light with god rays and dew sparkles, joyful wholesome vibe, 8K masterpiece.”

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Nano Banana 2 is best for

See all Use Cases

The model excels in Product, Branding, and Commercial categories with a 100% win rate and secures a #2 rank for text rendering at 93.5% accuracy. While dominant in commercial design and text integration, it shows comparatively lower performance in photorealism where it ranks #13 of 22 models.

Nano Banana 2 FAQ

How much does Nano Banana 2 cost?

Nano Banana 2 starts at $0.0225 per image through Lumenfall. Pricing varies by provider. Lumenfall does not add any markup to provider pricing.

What can Nano Banana 2 do?

Nano Banana 2 supports Function calling, Structured output, Batch, Streaming, System prompt, Tool use, Grounding, Thinking, Code execution, and Json mode. It accepts text, image, audio, video, and file input and produces text and image output.

How do I use Nano Banana 2 via API?

You can use Nano Banana 2 through Lumenfall's OpenAI-compatible API. Send requests to the unified endpoint with model ID "gemini-3.1-flash-image-preview". Code examples are available in Python, JavaScript, and cURL.

Which providers offer Nano Banana 2?

Nano Banana 2 is available through Replicate, Vertex AI, Gemini API, and fal.ai on Lumenfall. Lumenfall automatically routes requests to the best available provider.

Overview

Nano Banana 2 (slug: gemini-3.1-flash-image-preview) is a high-efficiency multimodal model developed by Google that bridges the gap between reasoning and visual synthesis. As the streamlined counterpart to the Gemini 3 Pro Image, it provides a unified interface for complex text generation and fast image creation. It is distinctive for its “Thinking Mode,” allowing the model to perform internal reasoning cycles before generating an image or structured text response.

Strengths

  • High-Efficiency Generation: Optimized for speed and low latency, making it suitable for real-time applications where rapid image iteration is required.
  • Complex Text Rendering: Excels at incorporating legible, accurate typography within generated images, a common failure point for many diffusion-based models.
  • Deep Reasoning Integration: Features a native thinking mode that allows the model to process complex prompts, spatial relationships, and logical constraints before producing visual or textual output.
  • Grounding and Tool Use: Supports search grounding and code execution, enabling the model to verify facts or perform calculations prior to generating content.
  • Reference Image Support: Capable of using existing images as structural or stylistic guides to maintain consistency across generated assets.

Limitations

  • Efficiency vs. Fidelity: While fast, it may lack the extreme aesthetic refinement and intricate textural detail found in the larger Gemini 3 Pro Image model.
  • Preview Status: As a preview release, the model may exhibit occasional inconsistencies in following highly nuanced stylistic prompts compared to more mature, production-stable versions.
  • Context Overhead: The use of internal reasoning (Thinking Mode) can increase processing time for simple tasks where a direct generation would have sufficed.

Technical Background

Part of the Gemini 3.1 Flash family, this model utilizes a multimodal transformer architecture trained for both discriminative and generative tasks. It integrates a latent diffusion-based image generation head directly into the language model pipeline, allowing for seamless transitions between modalities. By employing a “distilled” training approach, Google has optimized the model for high throughput while retaining the core reasoning capabilities of the Gemini 3.1 architecture.

Best For

Nano Banana 2 is ideal for building interactive design tools, rapid prototyping of social media assets, and automated content pipelines where both text and imagery are required. Its support for structured output and JSON mode makes it an excellent choice for developers needing to programmatically control visual attributes. You can experiment with these multimodal features and integrate them into your workflow through Lumenfall’s unified API and playground.

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