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Text Embedding V4

Alibaba (Qwen)

Knowledge search
model: text-embedding-v4
Try itDemo
Advanced parameters
⌘/Ctrl + Enter to send

Demo mode: doesn't call the upstream model. After signup with your key, the same request hits the real model.

Use cases

  • Enterprise search
  • High-accuracy RAG

Code samples

cURL
curl https://api.sealink.asia/v1/embeddings \
-H "Authorization: Bearer $SEALINK_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "text-embedding-v4",
"input": "SeaLink routes every model through one API."
}'
Python (OpenAI SDK)
from openai import OpenAI
client = OpenAI(base_url="https://api.sealink.asia/v1", api_key="<your-sealink-key>")
resp = client.embeddings.create(
model="text-embedding-v4",
input="SeaLink routes every model through one API.",
)
print(resp.data[0].embedding[:5])
Node.js (OpenAI SDK)
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.sealink.asia/v1",
apiKey: process.env.SEALINK_API_KEY,
});
const resp = await client.embeddings.create({
model: "text-embedding-v4",
input: "SeaLink routes every model through one API.",
});
console.log(resp.data[0].embedding.slice(0, 5));

Once you sign in, your base_url and API key will be inlined automatically.

Performance

Last 30 days from SeaLink's own probes; launch values use model-tier estimates until live probe history is available.

TTFT P50

426ms

TTFT P95

912ms

Tokens/sec

156

30d uptime

99.96%

Capabilities & limits

Context length
8K tokens
Capabilities
streaming
Status
operational