模型详情
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.
模型规格
- 上下文长度
- 8.191K
- 最大输出
- –
- 输入/输出模态
- 文本
- 发布日期
- 2025-10
02
API 端点
单一 MixRoute 网关，OpenAI 兼容
-
OpenAI-compatible
/v1/chat/completionsPOST
03
价格
固定费率，单位：/1M Tokens
输入
$0.1300 /1M Tokens
补全
$0.1300 /1M Tokens
05
选型摘要
快速判断是否适合你的工作负载
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
基于本页价格的实时估算，非实际账单
此模型没有缓存读取价格，不计算缓存费用
单一端点，可验证的决策
使用相同的请求格式测试此模型和备用路由
从真实工作负载开始，再由质量、总成本和故障条件决定是否接入生产流量。