Qwen: Qwen Image 3 Pro

Qwen-Image-3.0 Pro is Qwen’s flagship image generation and editing model for complex layouts, realistic detail and multilingual text. Use a precise brief or one to three references to create a graphic, product scene or focused visual edit.

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

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 Pro is Qwen’s flagship third-generation model for image generation and editing. It combines complex layout creation, detailed realistic textures, multilingual typography and close following of an image brief. Pro and the standard Qwen-Image-3.0 share the documented generation and editing modes; Pro emphasises image quality, while the standard edition balances quality and speed. The result is a rendered image artifact.

For an information-rich graphic, define the content before the look: the headline, supporting text, figures, hierarchy and relationship between sections. A useful product brief can combine a main object, close-up material details and labelled features on a single canvas. For an educational illustration, identify the concept, the diagram structure and the exact captions instead of relying on the model to invent the underlying facts. Complex layouts can also show several panels or nested interfaces. Keep the recommended 4,500-token prompt maximum focused on what must appear and where it belongs.

The 3.0 family supports native typography in 12 languages, multiple fonts and more than 100 artistic styles, along with fine textures such as hair, skin or fabric. Small-text rendering is demonstrated down to 10 pixels. This supports a design that blends lettering with a physical material or combines text with realistic imagery. Give the precise wording, numerals and language, and describe the typographic role of each block. A newspaper page or interface mockup is still a picture, so any later editable layout or interactive behavior is a separate artifact to build from it.

Pro can edit text within an image, add, delete or move elements, change a subject’s action, transfer visual style and enhance details. Editing accepts one to three input images with an instruction. Their order determines image 1, image 2 and image 3 in the brief. Specify which reference supplies the subject’s identity, which provides an object or clothing and which contributes a setting or pose. A focused edit names both the intended change and the features that should stay intact, making the resulting image easier to compare with the references.

Supported inputs are JPG, JPEG, PNG, BMP, TIFF, WebP and GIF, with only the first frame used for animated GIFs. Each input image can be up to 10 MB. The exact API accepts sides from 1 to 8,000 pixels and a long-to-short-side ratio no greater than 10:1; its recommended range is 384–2,048 pixels. The editing guide separately recommends images up to 3,072 pixels, so treat the input choice as preparation for the detail needed rather than a promise that every resolution improves the result. Use a legible, adequately framed reference for tiny text or material features.

Outputs are PNG. The producer workflow returns one to six alternatives, defaulting to one, and supports a total pixel area from 512 × 512 to 2,048 × 2,048 with aspect ratios from 1:8 to 8:1. The pixel-area budget permits some non-square dimensions whose longer side exceeds 2,048 pixels. When no size is specified, the model recommends a resolution based on the brief. Choose the shape for the actual placement, then compare the generated alternatives for content completeness, subject details and typography at the intended display size.

Intelligent prompt rewriting is enabled by default. Direct enhancement is available for both generation and editing, while agent enhancement refines text-to-image prompts and cannot be used for image-to-image editing. Thinking is also enabled by default and requires prompt rewriting; it adds reasoning work and generation time. Negative prompts identify unwanted elements, and an optional seed can help make comparisons between variants more consistent. A clear positive brief should still establish the subject, composition and details to preserve.

A practical result-review step checks the exact text, numbers, reading order, reference fidelity and edges or textures that matter to the design. When a specific part needs revision, retain the successful composition and describe the focused change. Keep all selected images with their prompt and references, since producer output locations expire after 24 hours. Pro’s documented modes and limits belong to the 3.0 edition; the ten-reference and native transparency features described for Qwen 2.1 are separate edition capabilities.

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

qwen/qwen-image-3-pro

Alibaba /qwen/qwen-image-3-pro

Overview

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

Field	Type	Requirement	Values & limits	Default
Field`model`	Type`string`	RequirementRequired	Values & limits qwen/qwen-image-3-pro	Default—
Field`prompt`	Type`string`	RequirementRequired	Values & limits Minimum length: 1	Default—
Field`resolution`	Type`string`	RequirementOptional	Values & limits 1K, 2K	Default—
Field`aspect_ratio`	Type`string`	RequirementOptional	Values & 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—
Field`n`	Type`integer`	RequirementOptional	Values & limits Minimum: 1 Maximum: 6	Default—
Field`input_references`	Type`array`	RequirementOptional	Values & limits Minimum items: 0 Maximum items: 4	Default—
Field`provider`	Type`object`	RequirementOptional	Values & limits	Default—

Method parameters and lifecycle

Parameter	Contract
Parameter`content_type`	Contractapplication/json
Parameter`required`	Contractmodel, prompt
Parameter`material_types`	Contracttext, 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.

Configuration	Rate schedule	Forecast quantity	Billing unit	Charge
ConfigurationBase token rates	Rate scheduleBase rate	Forecast 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 image	Rate schedule—	Forecast quantity—	Billing unitper input image	Charge Input · input image · Estimate for comparison only $0.006 per input image
ConfigurationEstimated generation cost	Rate schedule—	Forecast quantityone generation estimate	Billing unit—	Charge Output · Estimated generation cost · Estimate for comparison only $0.08 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-pro', '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}

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

Field	Type
Field`created`	Type
Field`data[].url`	Type
Field`data[].b64_json`	Type
Field`usage`	Type

Aliases

Model aliases

Ailoot Ultra qwen/qwen-image-3-pro

Method path aliases

/v1/images

Related caller IDs

qwen/qwen-image-3-pro

FAQ · Qwen: Qwen Image 3 Pro

What inputs and results are available?: POST /v1/images/generations · qwen/qwen-image-3-pro: text, image → image
Which fields does the request use?: POST /v1/images/generations · qwen/qwen-image-3-pro: model, prompt, resolution, aspect_ratio, n, input_references, provider
What limits apply?: POST /v1/images/generations · qwen/qwen-image-3-pro: n.minimum: 1; n.maximum: 6

Qwen: Qwen Image 3 Pro