Qwen3.7 Text Embedding
Qwen3.7 text embedding model converts text to dense vectors for retrieval, clustering and semantic matching. Billed by input characters at CNY 0.25 per million characters.
Supply channels
Direct official channels with shared authentication, billing and observability. Use the same API key as for other models.
Channels are ordered by request volume over the last 24 hours. A valid public provider name is shown when available; otherwise a generic channel label is used. Availability, latency and throughput use a rolling 24-hour window. Hourly colors show operational, degraded, down or no-traffic periods. Hover for actual values. The price is the same across channels.
Quick start
OpenAI compatible: change the base URL and set the model to qwen/qwen3.7-text-embedding.
from openai import OpenAI
client = OpenAI(
base_url="https://api.goodputai.cn/v1",
api_key="GOODPUT_API_KEY",
)
resp = client.embeddings.create(
model="qwen/qwen3.7-text-embedding",
input="West Lake, Hangzhou",
)
print(len(resp.data[0].embedding)) # Embedding dimensionsBilling method：Billed by input tokens only: CN¥0.25 per million tokens. No output charge.
Related models
Qwen text-to-image model. Billed per successfully generated image at CNY 0.2/image; failed generations are not billed.
Qwen speech recognition model. Accepts audio via base64 (≤10MB) or a public URL. Transcribed text output is not billed.
Qwen text-to-speech model. Billed by input characters at CNY 0.1 per 1,000 characters. Supports multiple voices via the voice parameter; default: Cherry.
Add Qwen3.7 Text Embedding to your app
Change the base URL and start calling after you sign up.