Qwen Image 2.1 vs Seedream 5.0 Flash

Qwen Image 2.1 and Seedream 5.0 Flash side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.

Alibaba Cloud ByteDance Image Generation

Qwen Image 2.1 vs Seedream 5.0 Flash at a glance

Qwen Image 2.1 from Alibaba Cloud and Seedream 5.0 Flash from ByteDance are both in the Image Generation category, available through the EmpirioLabs API.

Key differences

  • Qwen Image 2.1 is the newer release (Oct 2, 2026); Seedream 5.0 Flash was released on Sep 28, 2026.
  • Capabilities listed only for Qwen Image 2.1: multi image.
  • Capabilities listed only for Seedream 5.0 Flash: layer decomposition, interactive editing, multilingual text.

Qwen Image 2.1 vs Seedream 5.0 Flash: specs

SpecQwen Image 2.1Seedream 5.0 Flash
Model IDqwen-image-2-1seedream-5-0-flash
AuthorAlibaba CloudByteDance
ReleasedOct 2, 2026Sep 28, 2026
Input
Text Image
Text Image
Output
Image
Image
RegionSingaporeMalaysia
Endpoints
POST /v1/images/generations
POST /v1/images/generations
Capabilities
image generation image editing multi image multi reference transparent background text rendering
image generation image editing layer decomposition interactive editing multi reference text rendering multilingual text transparent background

Qwen Image 2.1 vs Seedream 5.0 Flash: API pricing

Live rates from the EmpirioLabs catalog for both models. Each rate card always matches what the API charges.

Qwen Image 2.1 vs Seedream 5.0 Flash: API parameters

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.

ParameterQwen Image 2.1Seedream 5.0 Flash
promptstringstring
model_variantqwen-image-2.1-pro, qwen-image-2.1-turbo Default: qwen-image-2.1-pro-
imagearrayarray
imagesarrayarray
aspect_ratioauto, 1:1, 16:9, 9:16, 3:2, 2:3, 4:3, 3:4, 5:4, 4:5 Default: autoauto, 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 21:9 Default: auto
resolutionauto, 1K, 2K Default: 2K-
sizestringstring
use_custom_sizeboolean Default: falseboolean Default: false
custom_width182 to 724015 to 8600
custom_height182 to 724015 to 8600
num_images1 to 6 Default: 1-
negative_promptstring-
prompt_extendboolean Default: true-
prompt_extend_modedirect, agent Default: direct-
seed0 to 2147483647-
watermarkboolean Default: falseboolean Default: false

Qwen Image 2.1 vs Seedream 5.0 Flash: limits and notes

Qwen Image 2.1

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.

Variants

  • Choose qwen-image-2.1-pro for the highest image quality and complex edits.
  • Choose qwen-image-2.1-turbo for faster, lower-cost generation and routine edits.
  • Choose with model_variant. Without it, the model id qwen-image-2.1-turbo runs Turbo and every other id of this model runs Pro.

Modes

  • Text to image from a prompt.
  • Image editing and reference-guided generation from one to ten images.
  • Direct prompt extension works for generation and editing. Agent prompt extension provides deeper refinement for text-to-image requests only.

Transparent images

  • Output images are PNG files. For a transparent background, set prompt_extend to false and describe the image in this form: "This is an RGBA image with transparency. A glass perfume bottle. The image has alpha channel and the background is transparent."

Output limits

  • One to six output images per request.
  • 1K, 2K, automatic, aspect-ratio presets, or an exact custom size.
  • Exact and custom sizes stay between 512x512 and 2560x2560 pixels in total area, with an aspect ratio from 1:8 to 8:1.

Billing

  • Each output image is billed at its variant's rate. Reference images are not billed.

Content safety

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.

Seedream 5.0 Flash

Modes

  • Text to image
  • Single or multi-image to image
  • Interactive editing with coordinate or sketch markers
  • Layer decomposition into a base image plus up to 16 layers

Interactive editing

Mark the region to change directly on the input image with a sketch, circle, or arrow, then describe it in the prompt. For exact placement, use coordinate tags on a 0 to 1000 normalized grid:

Place the subject from image 1 <bbox>179 283 796 986</bbox> at the position in image 2 <bbox>118 331 933 871</bbox>.

Layer decomposition

Set layer_decomposition to true with exactly one input image to split it into a base image plus up to 16 transparent PNG layers. Every returned image carries its stacking order as z_index, and each layer also carries its position in the base image as bounding_box.absolute and bounding_box.normalized, plus a name and a description. Leave the prompt empty to let the model choose the elements, or name the elements or coordinate regions to separate. Resolution accepts 1K, 1.5K, or 2K, and matches the input image when unset.

Limits

  • One output image per request, except layer decomposition, which returns the base image plus its layers
  • Up to 10 reference images, and exactly one for layer decomposition or a transparent background
  • 1K, 1.5K, and 2K resolution tiers
  • PNG or JPEG output, and layers are always PNG
  • A transparent background needs one input image that already has an alpha channel, and PNG output
  • No grouped output, streaming, or web search

Billing

Every resolution tier bills at the same per-image rate, and reference images are free. Layer decomposition bills every returned image, the base image and each layer, at that same rate.

Content safety

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.

How to call Qwen Image 2.1 and Seedream 5.0 Flash

Qwen Image 2.1 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 qwen-image-2-1 or seedream-5-0-flash. Get an API key from the EmpirioLabs dashboard.

cURL: submit the job
curl https://api.empiriolabs.ai/v1/images/generations \
  -H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-image-2-1",
    "prompt": "Describe what you want Qwen Image 2.1 to generate."
  }'

Qwen Image 2.1 vs Seedream 5.0 Flash: tests and guides

Prompt tests and comparison runs that cover both models.

Qwen Image 2.1 vs Seedream 5.0 Flash: common questions

What is the difference between Qwen Image 2.1 and Seedream 5.0 Flash?

Qwen Image 2.1 is the newer release (Oct 2, 2026); Seedream 5.0 Flash was released on Sep 28, 2026. Capabilities listed only for Qwen Image 2.1: multi image. Capabilities listed only for Seedream 5.0 Flash: layer decomposition, interactive editing, multilingual text. The specs, rate cards, and parameters on this page come from the live EmpirioLabs catalog.

Which is newer, Qwen Image 2.1 or Seedream 5.0 Flash?

Qwen Image 2.1 is the newer release (Oct 2, 2026); Seedream 5.0 Flash was released on Sep 28, 2026.

Which has the lower rate, Qwen Image 2.1 or Seedream 5.0 Flash?

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.

Can I switch between Qwen Image 2.1 and Seedream 5.0 Flash without rebuilding my integration?

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.

Can I try Qwen Image 2.1 and Seedream 5.0 Flash in the browser before integrating?

Yes. Open each model in the EmpirioLabs playground and run the same prompt on both, with the parameters the API exposes.

Ready to use better endpoints?

Check out our pricing or reach out if you want your own model deployed on our stack.