模型詳情
text-embedding-3-large
text-embedding-3-large is OpenAI's most capable embedding model for both english and non-english tasks. 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
$0.1300 /1M Tokens
補全
$0.1300 /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?
Most capable embedding model for search and similarity
Use text-embedding-3-large for semantic search, clustering, and recommendations across both English and non-English content. It produces high-dimensional embeddings for measuring text relatedness.
What should you check before using it?
Confirm embedding dimensions and pricing
text-embedding-3-large supports configurable embedding dimensions. Choose the dimension that balances accuracy and storage cost for your use case. Check the per-token pricing.
Why use it through MixRoute?
Use the compatible endpoint with stable model ID
Use the confirmed compatible endpoint with model ID text-embedding-3-large 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。