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Model facts & API quick start
Qwen-Image-2512 is served on Chutes inside a Trusted Execution Environment (TEE). Call it at https://vonkaiser-qwen-image-2512.chutes.ai/generate with a Chutes API key.
Qwen-Image-2512 at a glance
- Model ID
Qwen-Image-2512- Developer
- Qwen
- Deployed by
- vonkaiser
- Type
- Image
- Compute price
- $2.25 per hour
- Modalities
- text in → image out
- Confidential compute (TEE)
- Yes, runs in a Trusted Execution Environment
- Open weights
Qwen/Qwen-Image-2512- Architecture
- QwenImageTransformer2DModel diffusion transformer (60 layers, 24 heads, head dim 128) with a Qwen text encoder; diffusers text-to-image pipeline
- License
- Apache-2.0
- Released
- 2025-12
- Task
- Text-to-image generation
- Languages
- English and Chinese prompts
- Improvements over base Qwen-Image
- Enhanced human realism, finer natural detail, improved in-image text rendering (per model card)
- Benchmark
- Model card reports strongest open-source model on AI Arena blind T2I evaluations (10,000+ rounds)
- Output format on Chutes
- image/jpeg
API quick start
- Base URL
https://vonkaiser-qwen-image-2512.chutes.ai- Endpoint
POST /generate- Auth header
Authorization: Bearer $CHUTES_API_KEY
curl -X POST "https://vonkaiser-qwen-image-2512.chutes.ai/generate" \
-H "Authorization: Bearer $CHUTES_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "a serene mountain lake at sunset",
"seed": 42,
"width": 1024,
"height": 1024,
"true_cfg_scale": 4,
"negative_prompt": "",
"num_inference_steps": 30
}' \
--output output.jpgQwen-Image-2512 FAQ
What's new in Qwen-Image-2512 versus the original Qwen-Image?
Per the model card: markedly better human realism (less 'AI look', better skin, hair, and aged features), finer natural detail in landscapes and fur, and more accurate in-image text rendering and layout. The card reports it as the top open-source model in 10,000+ blind AI Arena comparisons at release.
What settings should I use?
The chute defaults to 30 steps and true_cfg_scale 4 at 1024x1024, which is a reasonable speed/quality balance. The model card's reference example uses 50 steps, true_cfg_scale 4.0, and larger aspect-ratio presets like 1328x1328 or 1664x928; move toward those for final-quality renders.
Does it support negative prompts?
Yes. The chute exposes negative_prompt (default empty). The model card itself uses a negative prompt targeting low resolution, deformed hands, over-saturation, waxy skin, and blurry text. Keep yours short and specific.
Can it render text inside images?
Yes, improved text rendering is one of the release's three headline upgrades, covering accuracy, layout, and combined text+image composition. Quote the exact wording you want in the prompt.
What license applies and can I use outputs commercially?
Apache-2.0, per the Hugging Face repo Qwen/Qwen-Image-2512. That permits commercial use, modification, and redistribution with attribution and license notice.
How do I call this chute from code?
POST a flat JSON body to https://vonkaiser-qwen-image-2512.chutes.ai/generate with an Authorization: Bearer header carrying your Chutes API key. The response body is the JPEG image itself; write it straight to a file.
Can I use it to edit an existing image?
No, this chute is text-to-image only and accepts no image input. For instruction-based editing with reference images, use the Qwen-Image-Edit-2511 chute.
Does it understand Chinese prompts?
Yes. The model is tagged for English and Chinese, and the model card's own examples include Chinese negative prompts. Both prompt and negative_prompt can be written in either language.