Qwen Image Edit
Neural Network
Qwen Image Edit is a Qwen model for image editing via description and precise text correction in images
Specifications
- Input
- text, images
- Output
- images
- File formats
- WEBP, JPG, PNG
How it works Qwen Image Edit?
Qwen Image Edit is a Qwen model for image editing via text description: upload an image, describe the edit, and get results without manual layer work. Its key feature, inherited from Qwen-Image, is accurate text rendering, now applied to editing, allowing precise text changes while preserving the frame's environment. In BotHub, the model is accessible from Russia without a VPN or foreign card; payment is in rubles, pay-as-you-go, no subscription needed. With over 250 neural networks in the same window, you can easily pass images to other models, and there is a unified OpenAI-compatible API for integration. Requests are encrypted with AES-GCM; contracts, invoices, EDI, and an admin panel with limits are available for companies. Useful for designers for quick layout iterations, marketers for creating creative series with different text, e-commerce teams for updating product card text, and developers for batch image processing via API.Frequently asked questions about Qwen Image Edit
You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.
This is a Qwen model for image generation and editing: it creates images from text descriptions and processes uploaded frames based on references. Suitable for object and background edits, cover variations, banners, product cards, and quick visual concepts.
You get a ready-made raster image that can be downloaded or passed on via API. Specific resolution and aspect ratio depend on your request and call parameters, so it's easier to check the result with a test generation in BotHub.
A separate step-by-step reasoning mode is not noted in our data: the model is focused on visual results, not text explanations. If you need a chain of thought before the image, prepare the prompt in a BotHub text model and then pass it here.
Function calling and structured output are not noted for this model in our data — its task is to output images. However, you can call it via the unified BotHub OpenAI-compatible API and build logic around it using a text model in the same integration.
Images, yes, this is the key scenario: you send a frame as a reference and describe the desired changes, receiving an updated version. Audio and video modes are not supported; BotHub has separate audio and video models for such tasks.
We have no specific data on the model's language capabilities, so rely on practice: formulate the task as specifically as possible and refine the prompt based on results. If the desired frame doesn't appear, it's easy to switch to another image generation model in the same BotHub window.