Nano Banana Pro vs Nano Banana 2: Which to Use?

Short answer: use Nano Banana 2 as your default for fast, high-volume image generation, and switch to Nano Banana Pro for final assets where fidelity, dense text and factual accuracy matter more than speed or cost. Google itself frames the split this way: Nano Banana 2 brings Pro-level world knowledge and quality "at lightning-fast speed", while Nano Banana Pro remains the choice for "high-fidelity tasks requiring maximum factual accuracy" (Google).

The naming is confusing, so here is the mapping. Nano Banana Pro is Gemini 3 Pro Image, announced on November 20, 2025 (Google). Nano Banana 2 is Gemini 3.1 Flash Image, announced on February 26, 2026 (Google). Despite the "2", Nano Banana 2 is not a successor to Pro. It is a newer Flash-tier model that brings most of Pro's features to a faster, cheaper tier. Both are available on APIMart through the same endpoint, so you can compare them with the same prompt before you commit.

Key Takeaways

• Nano Banana Pro is Gemini 3 Pro Image (November 2025); Nano Banana 2 is Gemini 3.1 Flash Image (February 2026).
• Google's list price is $0.134 per 1K or 2K image and $0.24 per 4K image for Pro, versus $0.067 (1K), $0.101 (2K) and $0.151 (4K) for Nano Banana 2.
• On APIMart's standard routes, Pro costs $0.03 (1K/2K) and $0.04 (4K) per image, while Nano Banana 2 costs $0.015 (1K), $0.02 (2K) and $0.025 (4K).
• Both accept up to 14 reference images, but Nano Banana 2 adds a 512px tier and four extreme aspect ratios (1:4, 4:1, 1:8, 8:1).
• Both can ground generations in Google Search; only Nano Banana 2 adds Google Image Search grounding.
• Google publishes no official latency figures for either model, but positions Nano Banana 2 as the faster one.

Nano Banana Pro vs Nano Banana 2 at a Glance

Capability rows come from Google's image generation docs and APIMart's API reference for Nano Banana Pro and Nano Banana 2.

What Are Nano Banana Pro and Nano Banana 2?

Nano Banana Pro: Gemini 3 Pro Image

Nano Banana Pro is built on Gemini 3 Pro and was launched as Google's studio-grade image generation and editing model. Google's developer announcement highlights "state-of-the-art text rendering", improved translation of text inside images, grounding with Google Search, and 2K and 4K output (Google). The same post is candid that it carries "higher cost and latency" than the earlier Flash image model, which is the trade-off you accept for its reasoning depth.

Google's current docs still describe Pro as "the premium choice for the most complex visual tasks" and recommend it for professional asset production (Google).

Nano Banana 2: Gemini 3.1 Flash Image

Nano Banana 2 brings "the high-speed intelligence of Gemini Flash to visual generation" (Google). It inherited the features that used to separate Pro from the original Nano Banana, including web-search grounding, legible text rendering, in-image translation and consistency for up to five characters and 14 objects. On top of that it added a 512px tier, four extreme aspect ratios and Image Search grounding.

When it launched, Google made Nano Banana 2 the default image model in the Gemini app across the Fast, Thinking and Pro modes, while Google AI Pro and Ultra subscribers kept access to Nano Banana Pro for specialized tasks. That rollout decision is a good signal of how Google itself sees the two: Nano Banana 2 for everyday work, Pro for the hard cases.

Why the names are confusing

The APIMart page slugs follow release order rather than Google's marketing names, so double-check the model ID in your request. The model field is what decides which model runs.

Image Quality and Text Rendering

How Google positions quality

Google does not publish a head-to-head quality benchmark between the two models, so any claim that one "wins" across the board is not officially confirmed. What Google does say is that Nano Banana 2 delivers "Pro-level intelligence and fidelity" (Google), while Pro remains reserved for tasks that need maximum factual accuracy and studio-quality control.

In practice the gap shows up on difficult prompts rather than simple ones. A product shot on a plain background looks good on either model. The difference tends to appear with dense layouts, many interacting subjects, precise diagrams and long passages of text, where Pro's larger reasoning model has more room to plan the image.

Text inside images

Both models are strong at typography, which is one of the main reasons teams choose the Nano Banana family. Pro's launch post claims state-of-the-art text rendering, and Nano Banana 2's launch post says it can "generate accurate, legible text for marketing mockups or greeting cards" and translate or localize text in an image.

A useful test is a prompt with several text blocks at different sizes:

A one-page restaurant menu for "Harbor Noodle Bar", cream paper, navy ink.
Header in bold serif. Three sections: Starters, Bowls, Drinks.
Each section lists 4 items with prices in USD and a one-line description.
Footer: "Open daily 11:00-22:00 · 18 Pier Street".

Run it on both models at 2K. If Nano Banana 2 gets every word and price right for your fonts and languages, you do not need to pay for Pro on that job. If small text breaks, move that job to Pro.

Speed and Thinking

What is officially known about speed

Neither Google's pricing page nor its docs publish a latency figure in seconds for either model, so exact generation times are not officially confirmed. Google describes Nano Banana 2 as delivering results "at lightning-fast speed", and its developer post quotes one customer, HubX, reporting a 74-76% reduction in latency in its face-editing workflow. Google also notes that the 512px tier "minimizes latency for rapid-fire iterations".

For Pro, Google states plainly that it carries higher cost and latency than Flash-tier image models. Real latency on any platform also depends on resolution, the number of reference images and queue load, so measure on your own workload.

Thinking levels

Both Gemini 3 image models are thinking models, and Google's docs say thinking "cannot be disabled in the API". The difference is control:

This is the core of the trade-off. Pro always reasons like a large model. Nano Banana 2 starts light and lets you raise the effort for complex prompts on Google's own API.

Resolution, Aspect Ratios and Reference Images

Output sizes

The extra formats matter for long banners, vertical infographics and timeline strips. Google added 4:1, 1:4, 8:1 and 1:8 with Nano Banana 2 (Google), and APIMart exposes all of them through the size field. If your layout needs an 8:1 web banner, Nano Banana 2 is the only one of the two that can produce it natively.

Reference images and consistency

Both models accept up to 14 reference images per request, but Google splits them differently:

Pro leans toward high-fidelity character work with up to five character references, while Nano Banana 2 favors object-heavy compositions such as product catalogs. On APIMart, Pro also accepts larger input files, which helps when your references are high-resolution photos that you do not want to recompress.

Search Grounding

Google Search on both models

Both models can use Google Search to pull in current facts before rendering, which is useful for weather cards, sports results, recipes or infographics about recent events. Google's Pro announcement describes using "grounding with Google Search to retrieve data based on the user's prompt", and Nano Banana 2 is "powered by real-time information and images from web search".

Image Search is Nano Banana 2 only

Google's docs say Image Search grounding is only available for the Nano Banana 2.1 and Gemini 3.1 Flash Image models, so Pro does not have it. With Image Search, the model can look up visual references for specific landmarks, products or species instead of relying only on what it learned in training.

On APIMart, the google_search and google_image_search parameters are documented for Nano Banana 2. The APIMart reference for Nano Banana Pro does not list a search parameter, so plan grounded jobs on Nano Banana 2.

{
  "model": "gemini-3.1-flash-image-preview",
  "prompt": "An infographic of this week's weather in Tokyo with daily highs and lows",
  "size": "16:9",
  "resolution": "2K",
  "google_search": true,
  "google_image_search": true
}

google_image_search must be used together with google_search: true.

Pricing Compared

Google list prices

Source: Gemini API pricing. Neither model has a free tier on the Gemini API, although Google AI Studio usage is free in supported regions. Note that Pro charges the same for 1K and 2K, so if you are already paying for Pro, rendering at 2K costs nothing extra.

APIMart prices

Prices below were read from the APIMart pricing API on October 9, 2026, at the default 20% discount. Check the model pages for current rates before you budget.

The official routes are billed 20% below Google's 1K, 2K and 4K list prices; on APIMart the official Nano Banana 2 route bills 0.5K at the same rate as 1K. Higher APIMart membership tiers raise the discount to 24% or 28%.

What 1,000 images cost

At 1K, Pro costs twice as much as Nano Banana 2. At 2K and 4K the gap narrows to about 1.5x on the standard routes, so if you mostly render at 2K, upgrading selected jobs to Pro is cheaper than the 1K numbers suggest.

How to Call Both Models on APIMart

Both models use POST https://api.apimart.ai/v1/images/generations, so switching is a one-line change to model.

Nano Banana Pro request

curl --request POST \
  --url https://api.apimart.ai/v1/images/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gemini-3-pro-image-preview",
    "prompt": "A detailed isometric cutaway of a coffee roastery with labeled machines",
    "n": 1,
    "size": "4:3",
    "resolution": "2K"
  }'

Nano Banana 2 request

curl --request POST \
  --url https://api.apimart.ai/v1/images/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gemini-3.1-flash-image-preview",
    "prompt": "A detailed isometric cutaway of a coffee roastery with labeled machines",
    "n": 1,
    "size": "4:3",
    "resolution": "2K"
  }'

To edit or composite, add image_urls with public URLs or full data URIs. The n field must be a plain number, not a quoted string. Use the -official model IDs when you need Google's official channel.

Getting the result

Both calls are asynchronous and return a task_id with status submitted. Poll GET https://api.apimart.ai/v1/tasks/{task_id} until the status is completed, then read the image links from data.result.images. Generated links are valid for 24 hours, so download the images you want to keep.

Which One Should You Use?

Choose Nano Banana 2 if

• You generate at volume and want the lowest per-image price ($0.015 at 1K on APIMart).
• You need 512px previews, or extreme formats such as 1:8 and 8:1.
• Your visuals depend on real-world references through Image Search grounding.
• You composite many products or objects (up to 10 object references).
• Latency matters, for example in interactive apps or rapid iteration loops.

Choose Nano Banana Pro if

• The image is a final asset where layout, dense text or diagram accuracy must be right the first time.
• You need up to five character references for consistent people across a series.
• Your reference photos are large files (up to 30MB each on APIMart).
• You render at 2K anyway, where Pro's price premium over Nano Banana 2 is smallest.

Or route between them

A practical pattern is to draft with Nano Banana 2 at 0.5K or 1K, pick the winning composition, and re-render only the finalists with Nano Banana Pro at 2K or 4K. Because both models share one endpoint and one API key on APIMart, that routing is a single field change. For a cross-vendor view, see GPT Image 2 vs Nano Banana 2, and for the cost logic behind routing, see multi-model API vs single model costs.

FAQs

Is Nano Banana 2 newer than Nano Banana Pro?

Yes. Nano Banana Pro (Gemini 3 Pro Image) was announced on November 20, 2025, and Nano Banana 2 (Gemini 3.1 Flash Image) on February 26, 2026. Nano Banana 2 is a newer Flash-tier model, not a replacement for Pro, and Google still offers Pro for high-fidelity work.

Is Nano Banana Pro better than Nano Banana 2?

Google positions Pro for "high-fidelity tasks requiring maximum factual accuracy" and Nano Banana 2 as Pro-level quality at Flash speed. Google has not published a head-to-head benchmark, so the best test is to run your own prompts on both and compare.

Which model is cheaper?

Nano Banana 2. Google lists it at $0.067 per 1K image versus $0.134 for Pro. On APIMart's standard routes, Nano Banana 2 costs $0.015 to $0.025 per image and Pro costs $0.03 to $0.04, depending on resolution.

Which model is faster?

Nano Banana 2 is designed to be faster, and Google describes Pro as carrying higher latency. Google does not publish official latency numbers for either model, so generation times are not officially confirmed and vary with resolution and the number of reference images.

How many reference images can each model use?

Both accept up to 14. Google's docs split Pro's limit into up to 6 object and 5 character images, and Nano Banana 2's into up to 10 object and 4 character images. On APIMart, Pro accepts files up to 30MB each and Nano Banana 2 up to 10MB each.

Do both models support Google Search grounding?

Both can ground generations in Google Search on Google's platform. Only Nano Banana 2 supports Image Search grounding. On APIMart, the google_search and google_image_search parameters are documented for Nano Banana 2.

Are the images watermarked?

Yes. Google's docs say all images generated by these models include an invisible SynthID watermark, and Google pairs SynthID with C2PA Content Credentials.

What to Watch Next

Google has already announced the next step in this line: Nano Banana 2.1, which Google's docs recommend for new projects and which adds mask-based editing (Google DeepMind). Google has also dropped the -preview suffix from both model IDs in its own docs, so watch for pricing and naming changes on every platform you use. Re-run your comparison prompts whenever a model updates, and re-check per-image prices on the model pages before you scale a workload.