模型詳情
text-embedding-3-small
text-embedding-3-small is OpenAI's improved, more performant version of the ada embedding model. Embeddings are a numerical representation of text that can be used to measure the relatedness between two pieces of text. Embeddings are useful for search, clustering, recommendations, anomaly detection, and classification tasks.
模型規格
- 上下文長度
- 8.191K
- 最大輸出
- –
- 輸入/輸出模態
- 文字
- 發布日期
- 2025-10
02
API 端點
單一 MixRoute 閘道，OpenAI 相容
-
OpenAI-compatible
/v1/chat/completionsPOST
03
價格
固定費率，單位：/1M Tokens
輸入
$0.0200 /1M Tokens
補全
$0.0200 /1M Tokens
05
選型摘要
快速判斷是否適合你的工作負載
What is this model good for?
Efficient embedding model for cost-sensitive workloads
Use text-embedding-3-small for embedding tasks where cost and speed are more important than maximum accuracy. It is an improved version of the ada embedding model.
What should you check before using it?
Compare accuracy vs text-embedding-3-large
text-embedding-3-small trades some accuracy for lower cost and faster performance. Test your specific use case to confirm the accuracy meets your requirements.
Why use it through MixRoute?
Use the compatible endpoint with stable model ID
Use the confirmed compatible endpoint with model ID text-embedding-3-small through MixRoute.
08
Token 成本估算
基於本頁價格的即時估算，非實際帳單
此模型沒有快取讀取價格，不計算快取費用
單一端點，可驗證的決策
使用相同的請求格式測試此模型與替代路由
從真實工作負載開始，再由品質、總成本與故障條件決定是否導入正式環境流量。