wan2.7-image-pro

Specs & limits

• Flagship Wan2.7 image model: color-palette control via hex codes for exact brand colors
• API-only via Model Studio

per Alibaba official docs ↗

One prompt, measured through the gateway

PROMPT A weathered enamel diner mug on a steel counter, the words "OPEN 24H" stencilled on the mug in worn paint, low winter sun raking in from the left, shallow depth of field.

wan2.7-image-pro

Model returned 1024×1024 latency 25 s

One prompt, one request per model, no retries and no cherry-picking - the first result each model returned. Neither size nor duration was pinned: each model used its own default, because a request shaped to fit all of them would flatter none. Files here are re-encoded for the web, so judge composition and prompt adherence, not compression.

Use wan2.7-image-pro in 30 seconds

OpenAI-compatible: swap the base_url, keep your SDK. POST /v1/images/generations

from openai import OpenAI

client = OpenAI(
    base_url="https://synthorai.io/v1",
    api_key="sk-syn-...",
)

resp = client.images.generate(
    model="wan2.7-image-pro",
    prompt="a watercolor lighthouse at dawn",
    size="1024x1024",
)
print(resp.data[0].b64_json[:80])

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://synthorai.io/v1",
  apiKey: "sk-syn-...",
});

const resp = await client.images.generate({
  model: "wan2.7-image-pro",
  prompt: "a watercolor lighthouse at dawn",
  size: "1024x1024",
});
console.log(resp.data?.[0]?.b64_json?.slice(0, 80));

curl https://synthorai.io/v1/images/generations \
  -H "Authorization: Bearer sk-syn-..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "wan2.7-image-pro",
    "prompt": "a watercolor lighthouse at dawn",
    "size": "1024x1024"
  }'

package main

import (
	"context"
	"fmt"

	"github.com/openai/openai-go/v3"
	"github.com/openai/openai-go/v3/option"
)

func main() {
	client := openai.NewClient(
		option.WithBaseURL("https://synthorai.io/v1"),
		option.WithAPIKey("sk-syn-..."),
	)
	resp, _ := client.Images.Generate(context.TODO(), openai.ImageGenerateParams{
		Model:  "wan2.7-image-pro",
		Prompt: "a watercolor lighthouse at dawn",
		Size:   "1024x1024",
	})
	fmt.Println(resp.Data[0].B64JSON[:80])
}

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.images.*;

OpenAIClient client = OpenAIOkHttpClient.builder()
    .baseUrl("https://synthorai.io/v1")
    .apiKey("sk-syn-...")
    .build();

ImagesResponse resp = client.images().generate(
    ImageGenerateParams.builder()
        .model("wan2.7-image-pro")
        .prompt("a watercolor lighthouse at dawn")
        .size("1024x1024")
        .build());
System.out.println(resp.data().orElseThrow().get(0).b64Json().orElseThrow().substring(0, 80));

About wan2.7-image-pro

• On top of that, the official docs give it 4K output for text-to-image work and an optional thinking mode that enhances inference to improve output quality at the cost of longer generation time; that thinking switch defaults to on for text-to-image, so the slower, better path is what you get unless you turn it off.
• Editing and image sets support up to 2K resolution.
• The 4K ceiling applies to text-to-image only, which is the precise shape of its advantage over the base variant rather than a blanket resolution win.
• Custom dimensions run from 768x768 to 4096x4096, aspect ratios from 1:8 to 8:1, prompts to 5,000 characters, and a call returns up to four images, or up to twelve when sequential image-set generation is enabled.
• Its headline controls are brand-oriented: a colour palette of three to ten hex values with proportions, print-quality text rendering, bounding-box interactive editing that takes up to two regions per image, and character consistency across a set.
• Negative prompts are not part of this line.
• Both synchronous and asynchronous task-based calling are documented, output is PNG with URLs expiring after twenty-four hours, and only successful images are billed.
• Synthorai serves the Pro variant through the same OpenAI-compatible API as the rest of its image catalog.

FAQ

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