

MOSS-Image Turbo and Qwen Image 2.1 side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.
MOSS-Image Turbo from OpenMOSS and Qwen Image 2.1 from Alibaba Cloud are both in the Image Generation category, available through the EmpirioLabs API.
| Spec | MOSS-Image Turbo | Qwen Image 2.1 |
|---|---|---|
| Model ID | moss-image-turbo | qwen-image-2-1 |
| Author | OpenMOSS | Alibaba Cloud |
| Released | Oct 16, 2026 | Oct 2, 2026 |
| Input | Text | Text Image |
| Output | Image | Image |
| Region | - | Singapore |
| Endpoints | POST /v1/images/generations | POST /v1/images/generations |
| Capabilities |
Live rates from the EmpirioLabs catalog for both models. Each rate card always matches what the API charges.
Request parameters each model lists on EmpirioLabs, with the allowed values or range where one applies. A dash marks a parameter the model does not list.
| Parameter | MOSS-Image Turbo | Qwen Image 2.1 |
|---|---|---|
| prompt | string | string |
| aspect_ratio | 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3 Default: 1:1 | auto, 1:1, 16:9, 9:16, 3:2, 2:3, 4:3, 3:4, 5:4, 4:5 Default: auto |
| size | string | string |
| width | 512 to 2048 | - |
| height | 512 to 2048 | - |
| seed | 0 to 2147483647 | 0 to 2147483647 |
| num_images | 1 to 4 Default: 1 | 1 to 6 Default: 1 |
| format | webp, png, jpg, jpeg Default: webp | - |
| response_format | url, b64_json Default: url | url, b64_json Default: url |
| return_base64 | boolean Default: false | - |
| model_variant | - | qwen-image-2.1-pro, qwen-image-2.1-turbo Default: qwen-image-2.1-pro |
| image | - | array |
| images | - | array |
| resolution | - | auto, 1K, 2K Default: 2K |
| use_custom_size | - | boolean Default: false |
| custom_width | - | 182 to 7240 |
Generates images from text, with accurate English and Chinese text in signs, posters, labels, and layouts.
Generated images pass an automated content-safety check. An image flagged as explicit is not returned. Because the image is generated before the check runs, a flagged generation is still billed.
Qwen Image 2.1 combines Pro and Turbo image generation and editing in one model. Pro is selected by default, output starts at 2K, and aspect ratio starts in Auto. Turbo provides a faster, lower-cost option.
Generated images pass an automated content-safety check. An image flagged as explicit is not returned. Because the image is generated before the check runs, a flagged generation is still billed.
MOSS-Image Turbo runs through POST /v1/images/generations. The request returns a job_id right away; poll GET /v1/jobs/{job_id} until the job completes and read the output URLs from the result. Or add "sync": true to skip polling: the request stays open and returns the finished OpenAI-style image response directly, so OpenAI SDKs work as-is. Both models are called through the same endpoint. Set model to moss-image-turbo or qwen-image-2-1. Get an API key from the EmpirioLabs dashboard.
curl https://api.empiriolabs.ai/v1/images/generations \
-H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "moss-image-turbo",
"prompt": "Describe what you want MOSS-Image Turbo to generate."
}'Prompt tests and comparison runs that cover both models.
MOSS-Image Turbo is the newer release (Oct 16, 2026); Qwen Image 2.1 was released on Oct 2, 2026. Input types only Qwen Image 2.1 accepts: Image. Capabilities listed only for MOSS-Image Turbo: multilingual text, seed control. The specs, rate cards, and parameters on this page come from the live EmpirioLabs catalog.
MOSS-Image Turbo is the newer release (Oct 16, 2026); Qwen Image 2.1 was released on Oct 2, 2026.
The two models are priced on different units or tiers, so compare the live rate cards on this page. They always match what the API charges.
Yes. Both models use POST /v1/images/generations with the same EmpirioLabs API key, so most integrations switch by changing the model value. Check the parameters table on this page first if you rely on a model-specific parameter.
Yes. Open each model in the EmpirioLabs playground and run the same prompt on both, with the parameters the API exposes.
Check out our pricing or reach out if you want your own model deployed on our stack.