Gemini 3.1 Flash Image, nicknamed Nano Banana 2, is Google DeepMind's latest generation AI image model built on the Gemini 3.1 Flash architecture. It is not simply a minor update to its predecessor. Nano Banana 2 is a ground-up rethinking of what a fast image model can deliver, closing the quality gap between the Flash and Pro tiers in measurable, practical ways.
Where the original Nano Banana established the concept and Nano Banana Pro pushed quality to its ceiling (at the cost of speed), Nano Banana 2 occupies a strategically important middle ground: it generates at native 2K resolution, produces legible multilingual text inside images, handles multi-character spatial scenes with physically coherent anatomy and lighting, and it does all of this faster and cheaper than Pro.
In several spatial reasoning benchmarks, Nano Banana 2 outperforms the flagship Pro model, making it the smarter default for volume-driven production workflows.
The three-tier Nano Banana family maps cleanly to different production needs. Here's how they differ in practice:
| Model | Best for | Resolution | Speed tier | Cost |
|---|---|---|---|---|
| Nano Banana | Fast drafting, prototypes | Standard | Fastest | Lowest |
| Nano Banana 2 ✦ | Production volume, text in images, pipelines | Native 2K | Flash | Mid-tier |
| Nano Banana Pro | Maximum photorealism, premium editorial | High | Slower | Higher |
Input: $0.325 / 1M tokens
Output: $78.00 / 1M tokens
Nano Banana 2 advances on three fronts that have historically been the weak points of fast image models: text rendering, style fidelity, and spatial coherence. Here's what that means for your builds.
Legible, stable typography inside generated images, across Latin, CJK, and other scripts. Posters, ad banners, and packaging mockups come out production-ready without manual Photoshop touchups.
Feed the model a visual reference and it accurately inherits the color palette, texture language, and compositional grammar across new generations. Essential for brand-consistent content at scale.
Multi-character scenes with physically plausible anatomy, correct shadows, accurate reflections, and realistic lighting. Nano Banana 2 beats Nano Banana Pro in several spatial coherence benchmarks.
Images generate at 2048-pixel resolution by default, no upscaling step required. Aspect ratio control covers square, portrait, and landscape, all at full resolution from the first call.
Localized, instruction-driven edits on existing images. Non-targeted regions stay intact. Supports inpainting masks for surgical precision, maintains facial identity across iterations.
Combine text instructions with a reference image in a single prompt. The model interprets both the semantic intent and the visual style simultaneously, without separate pipeline steps.
Nano Banana 2 ships with two production modes. Understanding which to use and when is the difference between smooth integration and wasted API calls.
This is the primary mode. Given a natural language description, the model synthesizes a brand-new image from scratch at native 2K resolution. There is no required input image, every pixel is constructed from the model's interpretation of your prompt. It's optimized for maximum throughput, making it the default choice for batch generation pipelines.
Editing mode takes a source image as its primary input and applies targeted, instruction-driven modifications. Rather than generating from nothing, the model reads the spatial structure, lighting, and semantic content of the input, then makes precise, localized changes while actively preserving everything you didn't ask it to change.
Pipeline tip: Nano Banana 2 pairs naturally as an upstream keyframe generator for video tools like Kling 3.0 or Sora 2. Its character consistency across prompts makes it ideal for pre-generating reference frames before handing off to a video generation model.
Nano Banana 2 is optimized for production workloads where both quality and throughput matter. Here are the teams getting the strongest results.
Generate large batches of ad creatives, UGC-style banners, and product visuals in minutes. The improved text rendering means typographic overlays — headlines, CTAs, promotional copy — are production-ready straight out of the API without a design revision round.
Automated product imagery, background replacement, lifestyle shot generation, and seasonal creative variations at scale. Nano Banana 2's style transfer capabilities make it easy to maintain visual brand consistency across thousands of SKUs.
Concept iteration that previously took hours can happen in seconds. Near-instant 2K output keeps creative momentum intact, no waiting for renders to come back before the next design decision can be made.
High-resolution output with reliable text rendering makes Nano Banana 2 ideal for cover art, thumbnails, social stories, and editorial illustrations. No design background required, just a well-written prompt and your API key.
Whether you're building a generative design tool, a custom avatar creator, or an image personalization feature inside a SaaS product, Nano Banana 2's fast inference and competitive pricing make it the right default for user-facing image generation endpoints.
Generating consistent keyframes for downstream video AI tools like Kling 3.0 or Sora 2 is a natural fit. Nano Banana 2's character consistency across prompt iterations makes it a reliable upstream component in short-form video and animation workflows.
Measured on the AI/ML API gateway across live traffic. Figures are medians unless stated. Last updated 2026-10-12.
Google documents Nano Banana 2 as suitable for creating infographics and turning notes into diagrams, using its real-world knowledge and web-search grounding to render specific subjects more accurately. It is also documented for rendering legible text directly into images, including greeting cards, marketing mockups, posters, and other text-heavy layouts.
Google also describes it as useful for high-volume developer image-generation workflows because it is optimized for speed and low latency. In addition, the model is positioned for image understanding and generation with image editing, including multi-turn editing and image generation from video input.
import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "google/gemini-3.1-flash-image", "messages": [ { "role": "user", "content": "Hello!" } ] }, ) print(r.json())
const r = await fetch("https://api.aimlapi.com/v1/chat/completions", { method: "POST", headers: { Authorization: `Bearer ${process.env.AIMLAPI_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ "model": "google/gemini-3.1-flash-image", "messages": [ { "role": "user", "content": "Hello!" } ] }), }); console.log(await r.json());
curl -X POST https://api.aimlapi.com/v1/chat/completions \ -H "Authorization: Bearer $AIMLAPI_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"google/gemini-3.1-flash-image","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Benchmark | Score | What it measures | Source | Retrieved |
|---|---|---|---|---|
| Image Editing Arena | 1105 | Human preference Elo from blind pairwise comparisons of edited images, measured independently by Artificial Analysis | Source | September 21, 2026 |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
| Reasoning + agents | ||||
| Reasoning + agents | ||||
| Balanced coding + agents | ||||
| Long-context, multimodal & agentic workflows | ||||
| Reasoning + agents |
Gemini 3.1 Flash Image (Nano Banana 2) has a 131,072 tokens context window and can return up to 32,768 tokens.
Gemini 3.1 Flash Image (Nano Banana 2) takes image, text as input and returns text.
Use google/gemini-3.1-flash-image as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
Gemini 3.1 Flash Image (Nano Banana 2) is priced at input $0.325 / 1M tokens, output $78 / 1M tokens.
Yes, Gemini 3.1 Flash Image (Nano Banana 2) can stream responses as they are generated.
Yes, Gemini 3.1 Flash Image (Nano Banana 2) accepts image input alongside text.
Gemini 3.1 Flash Image (Nano Banana 2) was built by Google.
It is a text-to-image model built for fast image generation from text prompts.
Yes, it lists web search as one of its supported features.
Yes, it supports function calling along with parallel tool calls and structured outputs.
