models

Qwen: Qwen Image 3

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Qwen: Qwen Image 3

Qwen-Image-3.0 combines image generation and editing for information-rich layouts, detailed scenes and multilingual typography. The standard edition balances quality and speed, accepting a text brief or up to three images with an editing instruction.

About the model

This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.

Qwen-Image-3.0 is Qwen’s third-generation image model, combining text-to-image creation and reference-based editing in one model. The standard edition balances image quality and response speed, while Qwen-Image-3.0 Pro is the flagship quality-oriented sibling. A request produces an image: a poster, illustrated explanation, product scene, storyboard or revised photograph rather than an editable document or a running interface.

Its rich-content capabilities suit a canvas with several related sections or a nested visual layout. Prepare the headings, exact wording, hierarchy and relationship between panels before adding stylistic detail. For a product comparison, a useful brief specifies the main product view, the attributes to label and the reading order of the supporting panels. For a storyboard, describe each panel’s subject, action and caption separately. The recommended prompt maximum is 4,500 tokens; spend that space on the content and layout the image actually needs.

The model supports detailed textures, typography down to small text demonstrated at 10 pixels, and native rendering across 12 languages with multiple fonts and artistic styles. Those capabilities can combine a realistic object with an information-rich graphic rather than forcing a choice between a photograph and a text-heavy layout. Supply the exact words and numerals to render, their intended language and where they belong. Treat a generated interface as a visual mockup: buttons, charts and labels in the image do not implement the behavior of an application.

Editing can change text, add or remove objects, move elements, adjust a subject’s action, transfer a style or enhance a damaged image’s details. Supply one to three images and a single clear editing instruction. Image numbering follows the supplied order, so identify which image contributes the subject, which provides a garment or object and which supplies the setting. For a product scene, ask to place the object from image 1 into the environment from image 2 while preserving the features that distinguish the product. Keep changes and preservation requirements explicit.

The exact image-input workflow accepts JPG, JPEG, PNG, BMP, TIFF, WebP and GIF; only the first frame of an animated GIF is processed. Each image can be up to 10 MB. The current API accepts dimensions from 1 to 8,000 pixels with no more than a 10:1 long-to-short-side ratio, and recommends 384–2,048 pixels for good results. Choose an input that clearly shows the details being transferred or edited. A tightly cropped reference can obscure the surrounding structure needed to place an object naturally.

The output is PNG, with one to six images per request and one as the default. Output pixel area ranges from 512 × 512 to 2,048 × 2,048, with aspect ratios between 1:8 and 8:1; these are area limits, not a rule that every side must be at most 2,048 pixels. If no size is supplied, the model recommends a resolution from the prompt. Select a landscape, square or portrait composition for the intended use, then inspect the returned image at that actual size so tiny labels and fine detail can be assessed where they will appear.

Prompt rewriting is enabled by default in the producer workflow. Direct enhancement works for both generation and editing; agent enhancement is a more elaborate rewriting mode for text-to-image only and is rejected for image-to-image editing. Thinking is enabled by default, requires prompt rewriting and increases generation time. Negative prompts can describe unwanted elements, while a fixed seed helps compare variations. State exclusions and exact preservation requirements clearly rather than expecting a seed to make a changing brief return an identical picture.

For a useful final artifact, inspect the rendered words, units, panel order and details that identify the subject, then revise the specific part that missed the brief. A multi-image response gives alternatives to compare; keep each returned image associated with the prompt and references that produced it. The producer’s image locations expire after 24 hours, so retain the actual image asset when the result becomes part of a project. The standard 3.0 edition remains distinct from Pro and from Qwen 2.1 models with their different reference counts and transparency features.

Ailoot Ultra · Images POST /v1/images/generations qwen/qwen-image-3

qwen/qwen-image-3

Alibaba /qwen/qwen-image-3

Overview

Qwen-Image-3.0 combines image generation and editing for information-rich layouts, detailed scenes and multilingual typography. The standard edition balances quality and speed, accepting a text brief or up to three images with an editing instruction.

Accepted inputs
Text · Images
Results
Images

Available in Ailoot · inputs & methods

Ailoot Ultra · Images POST /v1/images/generations
Input types
text, image
Output types
image
FieldTypeRequirementValues & limitsDefault
FieldmodelTypestringRequirementRequiredValues & limits
qwen/qwen-image-3
Default—
FieldpromptTypestringRequirementRequiredValues & limits
Minimum length: 1
Default—
FieldresolutionTypestringRequirementOptionalValues & limits
1K, 2K
Default—
Fieldaspect_ratioTypestringRequirementOptionalValues & limits
1:1, 1:2, 1:4, 2:1, 2:3, 3:2, 3:4, 4:1, 4:3, 4:5, 5:4, 9:16, 16:9
Default—
FieldnTypeintegerRequirementOptionalValues & limits
Minimum: 1
Maximum: 6
Default—
Fieldinput_referencesTypearrayRequirementOptionalValues & limits
Minimum items: 0
Maximum items: 4
Default—
FieldproviderTypeobjectRequirementOptionalValues & limitsDefault—
Method parameters and lifecycle
ParameterContract
Parametercontent_typeContractapplication/json
ParameterrequiredContractmodel, prompt
Parametermaterial_typesContracttext, image

Lifecycle: synchronous_result_then_owned_library

GET /v1/media/tasks/{task_id} · actual returned task_id or media library record

GET /v1/media/assets/{asset_id}/content

GET /v1/media/assets

GET /v1/media/assets/{asset_id}

Pricing

How the final charge is calculated

The displayed rates estimate the cost before generation. The final charge is calculated from the cost recorded for the original generation. Measured output duration and forecast quantities are not the final billable quantity.

Tariff references do not add request options. Supported parameters are listed for the selected method.

Fast mode
Not specified When fast mode is selected
Flex mode
Not specified When flex mode is selected
Maximum reasoning effort
Not specified When maximum reasoning effort uses the default adjustment

Estimated rates for comparison

Prices by configuration

Match each charge to the conditions shown. Use one rate for each set of alternative configurations.

ConfigurationRate scheduleForecast quantityBilling unitCharge
ConfigurationBase token ratesRate scheduleBase rateForecast quantity—Billing unit—Charge
Input · Input tokens · Estimate for comparison only — / 1K tokens
Output · Output tokens · Estimate for comparison only — / 1K tokens
Input · Cache read · Estimate for comparison only — / 1K tokens
Input · Cache write · Estimate for comparison only — / 1K tokens
Input · Cache write, 1 hour · Estimate for comparison only — / 1K tokens
Configurationinput imageRate schedule—Forecast quantity—Billing unitper input imageCharge
Input · input image · Estimate for comparison only $0.006 per input image
ConfigurationEstimated generation costRate schedule—Forecast quantityone generation estimateBilling unit—Charge
Output · Estimated generation cost · Estimate for comparison only $0.06 estimate before generation

This estimate is not an additional charge or a fixed rate for the completed generation.

Ailoot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →

Example requests

Ailoot Ultra · Images

curl
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
export AILOOT_API_KEY
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p={'model': 'qwen/qwen-image-3', 'prompt': 'a red panda astronaut floating in space, studio lighting'}

Path("request.json").write_text(json.dumps(p,ensure_ascii=False))
PY_REQUEST
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \
  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \
  --data-binary @request.json -D response-headers.txt -o result.json
python3 - <<'PY_RESULT'
import base64, json, os, subprocess
from pathlib import Path
from urllib.parse import urlsplit, urljoin

def save_images(items):
    if not items: raise SystemExit("No completed images; retain the full response")
    for index, item in enumerate(items):
        encoded=item.get("b64_json")
        uri=item.get("url", "")
        if not encoded and uri.startswith("data:image/"):
            header, separator, encoded=uri.partition(",")
            if not separator or ";base64" not in header: raise SystemExit("Unsupported image data URI")
        if encoded:
            raw=base64.b64decode(encoded,validate=True)
        elif uri:
            uri=urljoin("https://api.ailoot.ai",uri)
            parsed=urlsplit(uri)
            if parsed.scheme!="https" or not parsed.netloc or parsed.username or parsed.password:
                raise SystemExit("Invalid returned image URL")
            owned=parsed.netloc=="api.ailoot.ai" and parsed.path.startswith("/v1/media/assets/") and parsed.path.endswith("/content")
            args=["curl","--fail-with-body","--silent","--show-error",uri]
            if owned: args += ["-H","Authorization: Bearer "+os.environ["AILOOT_API_KEY"]]
            temporary=Path(f"image-{index}.bin")
            subprocess.run(args+["-o",str(temporary)],check=True)
            raw=temporary.read_bytes()
            temporary.unlink()
        else: raise SystemExit("Image has neither bytes nor URL")
        if not raw: raise SystemExit("Empty image result")
        ext="png" if raw.startswith(b"\x89PNG") else "jpg" if raw.startswith(b"\xff\xd8") else "webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else "svg" if raw.lstrip().startswith((b"<svg",b"<?xml")) else "bin"
        Path(f"image-{index}.{ext}").write_bytes(raw)
    print("Every returned image saved; complete response metadata retained")
save_images(json.loads(Path("result.json").read_text())["data"])
PY_RESULT

Receive and save results

Ailoot Ultra · Images

Download each returned image or save its Base64 contents

  • GET /v1/media/tasks/{task_id}
  • GET /v1/media/assets/{asset_id}/content
  • GET /v1/media/assets
  • GET /v1/media/assets/{asset_id}
Other content reads
Read existing owned assets
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \
  -H "Authorization: Bearer $AILOOT_API_KEY" -o owned-assets.json
# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.
Keep all completed results

Save every completed image; retrieve each returned URL or decode its Base64 contents.

Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.

If the original response needs checking

Keep the returned X-Client-Request-ID for reconciliation. Read only actual returned task_id/asset_id values or the owned media library; never build a task URL from the operation ID and never resubmit creation.

Response fields
FieldType
FieldcreatedType
Fielddata[].urlType
Fielddata[].b64_jsonType
FieldusageType

Aliases

Model aliases

Ailoot Ultra qwen/qwen-image-3

Method path aliases

/v1/images

Related caller IDs

qwen/qwen-image-3

FAQ · Qwen: Qwen Image 3
What inputs and results are available?

POST /v1/images/generations · qwen/qwen-image-3: text, image → image

Which fields does the request use?

POST /v1/images/generations · qwen/qwen-image-3: model, prompt, resolution, aspect_ratio, n, input_references, provider

What limits apply?

POST /v1/images/generations · qwen/qwen-image-3: n.minimum: 1; n.maximum: 6

More details

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The company and its project portfolio: millions of customers; monthly sales in the billions.

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