Qwen Image Edit VS Nano Banana: Detailed User or Hands-Free

Alibaba’s Qwen-Image-Edit (20B parameters) and Google’s Gemini 2.5 Flash Image (nicknamed Nano-Banana) are two advanced AI image models launched in mid-2025.

Qwen-Image-Edit is an open-source model, built on top of the Qwen-Image generation system, and focuses on text-driven image editing. In contrast, Google’s Nano-Banana is a proprietary model that supports both image generation and editing, available through Gemini’s API and user interface.

Both models enable rich image transformations, but they differ significantly in capabilities, output quality, performance, usability, licensing, and cost. The following sections provide a category-by-category comparison based on the requested framework.

Qwen-Image-Edit VS Nano Banana: Core Capabilities

Qwen-Image-Edit Specializes in image-to-image editing (input image + text instruction → modified image). Supports inpainting (add/remove objects) and limited outpainting. Text-to-image handled separately by Qwen-Image model. But Nano Banana can generate from text prompts, edit existing images, and perform multi-image fusion (merging several photos).

Category	Qwen-Image-Edit	Nano-Banana
Semantic Editing	Yes — object rotation (even novel 90°/180° views), style transfer, IP conversion.	Yes — scene/style changes, pose adjustments, blending multiple styles or sources in one prompt.
Appearance Editing	Yes — fine-grained edits (add signs with reflections, remove stray hair, change clothing, replace backgrounds).	Yes — natural language edits (blur background, relocate objects, recolor elements).
Text Editing	Strong support — precise English & Chinese text editing (insert/remove/modify) while preserving font, size, and layout.	Weak support — not designed for reliable in-image text editing; behaves like most generative models, struggles with accurate text layouts.
Consistency	Explicitly designed for character consistency (e.g. Qwen mascot across outfits and settings).	Maintains subject consistency across edits (faces, animals, objects)

Qwen-Image-Edit

• You provide one input image + a text instruction.
• It lets you selectively add, remove, or modify specific objects or regions while keeping the rest untouched.

Nano-Banana

• It can take a text prompt alone, or one or several images as inputs.
• With multi-image fusion, you can supply multiple photos or elements, and the model decides how to arrange, blend, and place those objects in a coherent scene.

Qwen-Image-Edit VS Nano Banana: Output Quality

• Gemini 2.5 Flash Image is the stronger all-rounder, particularly excelling in characters, creativity, and overall preference.
• Qwen Image Edit has a niche advantage in stylization, making it attractive for scenarios where style fidelity or artistic expression is more important.

However, Banana may be less effective in text generation, and there are currently no concrete data available. In contrast, Qwen’s results on LongText-Bench, ChineseWord, and TextCraft demonstrate that it excels in text rendering—particularly in Chinese text generation—outperforming existing state-of-the-art models by a significant margin.

Qwen-Image-Edit VS Nano Banana: Speed

Nano Banana

• Reported Speed: ~20 seconds per image on Google’s servers
• Consistency: Since it runs exclusively on Google Cloud TPUs/GPUs, the speed is relatively stable for end users.
• Limitation: Users cannot tune or optimize performance locally, as the model is only accessible via Google’s API/Studio.

Qwen-Image-Edit

• Reported Speed: ~20 seconds per edit on a good GPU
• Flexibility: Performance varies depending on hardware (GPU model, VRAM size, batch size, resolution).
• Local & Cloud Deployment: Can run locally if you have sufficient GPU memory, or on various cloud providers.

It is a large 20B parameter model that requires substantial GPU memory. Performance depends on deployment choices: full-precision models need more than 32GB of VRAM, while compressed or quantized versions can run on 24GB or even around 16GB of VRAM.

Qwen-Image-Edit VS Nano Banana: Ease of Use

Interfaces / Integration

• Qwen-Image-Edit
  • Available via Qwen Chat (web UI)
  • Can be run via code, API, or demo UIs.
  • Hugging face or ComfyUI node.
• Nano Banana
  • Integrated into Google’s Gemini app (mobile + web).
  • Available to developers via Gemini API,
  • Appearing on third-party platforms (OpenRouter.ai, Fal.ai) via Gemini API.
  • No public weights or ComfyUI node available.

Prompt Difficulty

• Qwen-Image-Edit
  • Handles simple natural prompts
  • Good at iterative refinement （step by step）
• Nano Banana
  • Works with plain descriptive prompts
  • Noted for understanding complex, multi-step prompts in one go.

Ecosystem

• Qwen-Image-Edit
  • Open-source model → community can develop LoRAs, ControlNets, GUIs.
  • Already has Diffusers scripts and example workflows.
  • Strong potential for community-driven expansion.
• Nano Banana
  • Closed-source → no weights or public code.
  • Ecosystem limited to Google + partners.
  • Some external tools exist, but only as wrappers around Google’s API.

Qwen-Image-Edit VS Nano Banana: Application

Style Change:

turn this photo into a character figure. Behind it, place a box with the character’s image printed on it, and a computer showing the Blender modeling process on its screen. In front of the box, add a round plastic base with the character figure standing on

Image Edit:

Edit the sky above the bridge into beautiful fiery clouds

Text Edit:

Make a fashion magazine cover with a woman posing in a red dress, the title of the magazine is Qwen Image Edit, no other text

Multi Image Fusion:

Best Practices for Qwen-Image-Edit

Novita launches the Qwen-Image-Edit API, with pricing at just $0.02 per image.

Step 1: Log In and Access the Model Library

Log in to your account and click on the Model Library button.

Step 2: Choose Your Model

Browse through the available options and select the model that suits your needs.

Step 3: Get Your API Key

To authenticate with the API, we will provide you with a new API key. Entering the “Settings“ page, you can copy the API key as indicated in the image.

Step 4: Install the API

Install API using the package manager specific to your programming language.

After installation, import the necessary libraries into your development environment. Initialize the API with your API key to start interacting with Novita AI LLM. This is an example of using chat completions API for python users.

Qwen-Image-Edit to Video API Example

import requests

url = "https://api.novita.ai/v3/async/qwen-image-edit"

payload = {
    "prompt": "<string>",
    "image": "<string>",
    "seed": 123,
    "output_format": "<string>"
}
headers = {
    "Content-Type": "<content-type>",
    "Authorization": "<authorization>"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())

Extrct Image URL

import requests

url = "https://api.novita.ai/v3/async/task-result"

headers = {
    "Content-Type": "<content-type>",
    "Authorization": "<authorization>"
}

response = requests.get(url, headers=headers)

print(response.json())

Alibaba’s Qwen-Image-Edit and Google’s Gemini 2.5 Flash Image (Nano-Banana) represent two different approaches to next-generation image AI in 2025.

• Qwen-Image-Edit excels in fine-grained, text-driven editing (object replacement, inpainting, text editing, stylization). It is open-source, highly customizable, and supported by an expanding community ecosystem. Its major strengths are stylization quality, precise text editing (especially Chinese), and flexible deployment options. However, it requires large GPUs (20B parameters), with performance depending on quantization and hardware configuration.
• Nano-Banana (Gemini 2.5 Flash Image) is a closed, cloud-only model designed for end-to-end generation and editing, including multi-image fusion. It performs strongly in overall preference, creativity, and character rendering, while being easy to use via Google’s ecosystem (Gemini app, API, Studio, Vertex AI). Its strengths lie in complex, multi-step prompt understanding and seamless integration, but it lacks open weights, advanced text editing capabilities, and community-driven innovation.

In short:

• Qwen-Image-Edit is best for open-source developers, research, and creative stylization workflows.
• Nano-Banana is best for plug-and-play use cases, professional content creation, and Google-integrated applications.

Frequently Asked Questions

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