Qwen (T2I) is an AI model (prompt to image) available on Artifio.ai through Qwen. You can run it in our workspace from a single shared wallet and download your outputs.

How much does Qwen (T2I) cost on Artifio?

Qwen (T2I) starts at about $0.005 per generation on Artifio.ai. The exact cost is shown in the workspace before you confirm and can vary with the options you select.

How do I use Qwen (T2I) on Artifio?

Click Generate Now to open the workspace at /create/qwen-text-to-image. Fill in the form fields, review the live cost estimate, and run your generation.

What kind of outputs does Qwen (T2I) produce?

Qwen (T2I) is configured for prompt to image workflows in the image category. See the technical parameters below for supported inputs and options.

Can I try Qwen (T2I) for free?

Sign up free, top up your wallet from $5, and you can run Qwen (T2I) pay-as-you-go without a separate subscription for this model.

Qwen (T2I) — AI Image Generator

Name: Qwen (T2I)
Brand: Artifio
Price: 0.005 USD
Availability: InStock

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Qwen (T2I) — AI Image Generator | Artifio.ai

About Qwen (T2I)

Qwen (T2I) runs Qwen-Image, the 20B-parameter MMDiT image foundation model that Alibaba's Qwen team released under Apache 2.0 on August 4, 2025. It was built for one problem in particular: putting legible, correctly spelled text inside generated images, from single-word signage to multi-line paragraph layouts, in both English and Chinese. The technical report pairs the diffusion backbone with a Qwen2.5-VL text encoder and a curriculum that trains from simple captions up to paragraph-level descriptions.

The same repository line later received the Qwen-Image-2512 refresh (December 31, 2025), which Alibaba's changelog says improved human realism and texture quality. On Artifio the model sits in one workspace beside 100+ others, paid per generation from a single wallet with no per-model subscription.

Features

20B-parameter MMDiT architecture with a Qwen2.5-VL encoder, released with open Apache 2.0 weights on Hugging Face and ModelScope
Complex text rendering inside images: multi-line layouts, paragraph-level semantics, and fine-grained typographic detail in English and Chinese
Seven official aspect-ratio presets, from 1328x1328 (1:1) through 1664x928 (16:9), 928x1664 (9:16), 4:3, 3:4, 3:2, and 2:3
Style range covering photorealism, anime, and illustration from the same checkpoint
Training recipe documented in a public technical report (arXiv 2508.02324), including the data pipeline for text-rendering supervision
Family refresh Qwen-Image-2512 (December 2025) targeting human realism and texture quality

What people use it for

Posters, slides, and infographics where the headline and body text must come out readable on the first pass
Bilingual marketing assets that mix Chinese and English typography in one image
Product and brand mockups with embedded labels, signage, or packaging text
General text-to-image work across photoreal and anime styles without switching checkpoints
Storyboard and comic frames where captions belong inside the picture

Reported strengths

Chinese text generation outperformed existing state-of-the-art models by a significant margin at release, per the launch report
Benchmark results across GenEval, DPG, and OneIG-Bench placed it ahead of contemporary open models on general generation as well as on text
Apache 2.0 licensing keeps the weights inspectable and commercially usable
One model covers a wide stylistic spread, which cuts the need to route prompts between specialist checkpoints

Reported limitations

Official generation presets top out around 1.4 megapixels (1328x1328 at 1:1); native 2K output only arrived with the separate Qwen-Image-2.0 generation in February 2026
Alibaba's own Qwen-Image-2512 release notes list enhanced human realism and texture among the fixes, which points at soft spots in the original August 2025 weights for faces and skin
At 20 billion parameters the checkpoint is one of the heavier open image models, so full-precision local inference needs high-end GPU memory

Sources

Qwen-Image: Crafting with Native Text Rendering (Qwen (Alibaba))
Qwen/Qwen-Image model card (Hugging Face (Qwen))
Qwen-Image Technical Report (arXiv)
QwenLM/Qwen-Image repository (GitHub (QwenLM))