Alibaba (Qwen) / tongyi-embedding-vision-plus
Tongyi Embedding Vision Plus
Tongyi Embedding Vision Plus turns text into embeddings for semantic search, RAG retrieval, clustering, and similarity matching.
Context
4K
tokens
Input
$0.108
/ 1M tokens
Output
$0.108
/ 1M tokens
Quality
#54
Elo 1200
Overview
What this model is good for
Tongyi Embedding Vision Plus turns text into embeddings for semantic search, RAG retrieval, clustering, and similarity matching.
Model capabilities
Multimodal
Accepts text and image input in one request, useful for visual understanding, screenshots, and mixed-context tasks.
Model maker
Model maker and access
This section shows the model maker, SeaLink model ID, protocol, and pricing information.
Alibaba (Qwen)
Called through SeaLink's unified account, balance, and OpenAI-compatible API.
Protocol
Embeddings API
Base URL: https://test.sealink.io/v1
Pricing
Pricing and cost sense
Prices come from the current model catalog. Simple estimates help users judge whether the model fits production volume.
Light production run
100K input + 25K output
$0.014
Higher-volume run
1M input + 250K output
$0.135
Actual billing follows usage logs and billing records; caching and media pricing depend on the endpoint.
API
Copy into your code
The model page should make it clear which model to copy, which base URL to use, and where to get an API Key.
model
tongyi-embedding-vision-plusbase_url
https://test.sealink.io/v1Auth
Bearer $SEALINK_API_KEYcurl https://test.sealink.io/v1/embeddings \-H "Authorization: Bearer $SEALINK_API_KEY" \-H "Content-Type: application/json" \-d '{"model": "tongyi-embedding-vision-plus","input": "SeaLink gives you one API for leading AI models."}'
from openai import OpenAIclient = OpenAI(base_url="https://test.sealink.io/v1", api_key="<your-sealink-key>")resp = client.embeddings.create(model="tongyi-embedding-vision-plus",input="SeaLink gives you one API for leading AI models.",)print(resp.data[0].embedding[:5])
import OpenAI from "openai";const client = new OpenAI({baseURL: "https://test.sealink.io/v1",apiKey: process.env.SEALINK_API_KEY,});const resp = await client.embeddings.create({model: "tongyi-embedding-vision-plus",input: "SeaLink gives you one API for leading AI models.",});console.log(resp.data[0].embedding.slice(0, 5));