Alibaba Wan 2.6 Text To Image

Alibaba Wan 2.6 Text To Image

Playground

Alibaba WAN 2.6 Text-to-Image turns text prompts into AI-generated images with the WAN 2.6 model for on-demand image creation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Alibaba Wan 2.6 Text-to-Image

Wan 2.6 Text-to-Image is Alibaba’s text-to-image model for generating PNG images from a single prompt. It’s designed for practical creative workflows—concept art, product visuals, portraits, and stylized imagery—where you want strong prompt adherence plus flexible output sizing.

Key capabilities

• Single-request (synchronous) generation Generate images and get results back in one request (no separate polling flow).

• Flexible custom dimensions Choose width*height freely as long as the total pixel area stays within the allowed range and the aspect ratio is within [1:4, 4:1].

• Prompt rewriting via prompt_extend Optional prompt expansion can improve results for short/simple prompts (at the cost of a few extra seconds).

• Negative prompting for tighter control Use negative_prompt to suppress unwanted artifacts (e.g., “blurry, low quality, extra fingers”).

• Batch generation (n images per run) Generate 1–4 images per request; n directly affects cost (price scales with image count).

• Reproducibility with seed Set seed for more consistent outputs across runs (results may still vary slightly).

• Optional watermark control Toggle an “AI-generated” watermark in the lower-right corner.

Parameters and how to use

• prompt: (required) The text instruction describing the image you want.
• negative_prompt: What you want to avoid in the output image.
• size: Output resolution as width*height.
• n: Number of images to generate (1–4).
• prompt_extend: Enable/disable prompt rewriting.
• watermark: Enable/disable watermark.
• seed: Random seed for more consistent results.

Prompt

Write prompts that are concrete and visual:

• Start with subject + setting + style: “A modern tea shop interior, warm afternoon light, minimalist wood design, cinematic photography”
• Add composition/camera when you care about framing: “medium shot, shallow depth of field, 35mm look”
• If you need cleaner outputs, pair with a short negative prompt: “blurry, low-res, watermark, extra limbs, distorted hands”
• Prompt language: Chinese and English are supported; prompts longer than the documented limit may be truncated.

Other parameters

1. prompt (required) The positive prompt text that describes the content, style, and composition.

2. size Format: width*height.

   • For wan2.6-t2i, total pixels must be between 768×768 and 1440×1440, and aspect ratio must be within [1:4, 4:1]. Common starting points:
   • 1:1 → 1280*1280 or 1024*1024
   • 16:9 → 1280*720
   • 9:16 → 720*1280

3. negative_prompt Short list of undesired attributes. Max length is limited by the upstream API (extra text may be truncated).

4. enable_prompt_expansion

   • true (default): improves results for short prompts; adds latency (often a few seconds).
   • false: faster; you control all detail manually.

5. seed Integer in [0, 2147483647]. Use a fixed seed to reduce randomness; omit for fresh variations each run.

After you finish configuring the parameters, click Run, preview the result, and iterate if needed.

Pricing

Each run cost $0.03.

Notes

• If you turn on enable_prompt_expansion, expect slightly higher latency; it’s best when your prompt is short or under-specified.
• The image URLs returned by the upstream API may be time-limited—download and store outputs promptly if you need to keep them.

Related Models

• Alibaba Wan 2.5 (Text-to-Image) – A proven, cost-stable Wan text-to-image option with a similar workflow.
• WaveSpeedAI FLUX 2 Turbo (Edit) – Better fit when you need instruction-following edits on an existing image.
• Google Nano Banana Pro (Edit) – Strong prompt-based image editing with reliable composition control.
• ByteDance Seedream V4 (Text-to-Image) – A solid alternative for stylized generation and fast iteration.

# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/alibaba/wan-2.6/text-to-image" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "size": "1024*1024",
    "enable_prompt_expansion": false,
    "seed": -1
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"