alibaba/wan-2.7/text-to-image

alibaba/wan-2.7/text-to-image

WAN 2.7 Text-to-Image generates high-quality images from text prompts with thinking mode for enhanced image quality. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Examples

alibaba/wan-2.7/text-to-image Examples 1

Parameters

NameTypeDefaultConstraintsDescription
prompt *Prompttextarea—≤ 5000 charsThe positive prompt for the generation.
sizeSizetext1024*1024≤ 500 charsThe size of the generated image in pixels (width*height). Range: 512-4096 per dimension. Total pixels must be between 768*768 and 2048*2048. Aspect ratio must be between 1:8 and 8:1.
thinking_modeThinking Modebooleantrue—Enable thinking mode for enhanced reasoning and better image quality. Increases generation time.

Output fields

FieldTypeDescription
imagesarray<string>Generated image URL(s).

API

Call this model through one unified REST API. Get a key on the API Keys page.

cURL
# 1) Submit — returns { "task_uuid": "..." }
curl -X POST "https://www.namifusion.com/api/v1/marketplace/run/alibaba/wan-2.7/text-to-image" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "input": {
    "prompt": "A cinematic portrait in a futuristic botanical garden at dusk, soft rim light, intricate details, photorealistic, shallow depth of field.",
    "size": "1024*1024",
    "thinking_mode": true
  }
}'

# 2) Poll until status is "completed", then read the output URLs
curl "https://www.namifusion.com/api/v1/marketplace/run/tasks/TASK_UUID" \
  -H "Authorization: Bearer YOUR_API_KEY"
Python
import time, requests

API_KEY = "YOUR_API_KEY"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

# 1) Submit
resp = requests.post(
    "https://www.namifusion.com/api/v1/marketplace/run/alibaba/wan-2.7/text-to-image",
    headers=HEADERS,
    json={
        "input": {
            "prompt": "A cinematic portrait in a futuristic botanical garden at dusk, soft rim light, intricate details, photorealistic, shallow depth of field.",
            "size": "1024*1024",
            "thinking_mode": True
        }
    },
)
resp.raise_for_status()  # 401/402/429/5xx stop here instead of polling a bad task
task = resp.json()

# 2) Poll until a terminal state (completed / failed / cancelled).
#    This model is allowed up to 300s server-side.
deadline = time.time() + 360
while task.get("status") not in ("completed", "failed", "cancelled"):
    if time.time() > deadline:
        raise TimeoutError(f"still {task.get('status')} — keep the task_uuid and poll later")
    time.sleep(3)
    poll = requests.get(f"https://www.namifusion.com/api/v1/marketplace/run/tasks/{task['task_uuid']}", headers=HEADERS)
    poll.raise_for_status()
    task = poll.json()

print(task["status"], task.get("output"))
JavaScript
const API_KEY = "YOUR_API_KEY";
const HEADERS = { Authorization: `Bearer ${API_KEY}` };

// 1) Submit
const resp = await fetch("https://www.namifusion.com/api/v1/marketplace/run/alibaba/wan-2.7/text-to-image", {
  method: "POST",
  headers: { ...HEADERS, "Content-Type": "application/json" },
  body: JSON.stringify({
    "input": {
      "prompt": "A cinematic portrait in a futuristic botanical garden at dusk, soft rim light, intricate details, photorealistic, shallow depth of field.",
      "size": "1024*1024",
      "thinking_mode": true
    }
  }),
});
if (!resp.ok) throw new Error(`submit failed: ${resp.status} ${await resp.text()}`);
let task = await resp.json();

// 2) Poll until a terminal state (completed / failed / cancelled).
//    This model is allowed up to 300s server-side.
const deadline = Date.now() + 360 * 1000;
while (!["completed", "failed", "cancelled"].includes(task.status)) {
  if (Date.now() > deadline) throw new Error(`still ${task.status} — keep the task_uuid and poll later`);
  await new Promise((r) => setTimeout(r, 3000));
  const poll = await fetch(`https://www.namifusion.com/api/v1/marketplace/run/tasks/${task.task_uuid}`, { headers: HEADERS });
  if (!poll.ok) throw new Error(`poll failed: ${poll.status}`);
  task = await poll.json();
}

console.log(task.status, task.output);

Documentation

alibaba/wan-2.7/text-to-image

High-quality text-to-image generation with thinking mode, flexible sizing, and no cold starts.

alibaba/wan-2.7/text-to-image is a production-ready text-to-image model designed to generate detailed, visually coherent images from natural language prompts. It combines strong prompt understanding, flexible output sizing, and affordable per-image pricing, making it well suited for creative, marketing, and commercial workflows.

🚀 Key Features

  • High-quality image generation: Produces detailed, visually consistent images with strong composition, lighting, and texture.
  • Thinking mode for better results: Built-in thinking mode improves prompt reasoning and adherence, helping the model generate more coherent outputs.
  • Flexible size control: Supports custom output dimensions from 512 to 4096 pixels per side for a wide range of delivery formats.
  • Broad aspect ratio support: Handles aspect ratios from 1:8 to 8:1, covering square, portrait, landscape, and widescreen layouts.
  • No cold starts: Suitable for responsive production workflows where predictable availability and fast task startup matter.

🛠️ Technical Specifications

ItemDetails
Model Namealibaba/wan-2.7/text-to-image
Model TypeText-to-image
ArchitectureWan 2.7 text-to-image generation architecture
InputText Prompt
OutputImage
Default Resolution1024×1024
Resolution Range512–4096 pixels per dimension
Total Pixel ConstraintTotal pixels must be between 768×768 and 2048×2048
Aspect Ratio1:8 to 8:1
Thinking ModeSupported, enabled by default; improves quality with higher latency
LatencyStandard generation is faster; thinking mode increases generation time
Output FormatGenerated image

Sample Prompts

  • A modern tea shop interior, warm afternoon light, minimalist wood design, cinematic photography
  • A cinematic ocean wave at sunrise, highly detailed, dramatic lighting, ultra realistic
  • A futuristic fashion portrait, neon city background, editorial style, sharp focus

💰 Pricing

ItemPrice
Per generated image$0.03

💡 Best Use Cases

  • Social media content: Create platform-ready visuals across square, portrait, and landscape formats.
  • Marketing and advertising: Generate campaign concepts, branded visuals, and promotional assets without a photoshoot.
  • Concept art and storyboarding: Rapidly visualize scenes, characters, and environments from text descriptions.
  • E-commerce imagery: Produce product lifestyle visuals and storefront-ready creative assets efficiently.

🔗 Related Models

  • Wan 2.7 Text-to-Image Pro: A higher-end version for more demanding production workflows and higher-resolution output.
  • Wan 2.6 Text-to-Image: Previous-generation Wan text-to-image model.
  • Seedream V4 Text-to-Image: Suitable for style-consistent poster, campaign, and brand-oriented image generation.
  • FLUX.2 Dev Text-to-Image: Strong prompt adherence and fine detail for creative and production use cases.

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