Routin
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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.
同系列或更低输入价的公开模型。 / Same provider or cheaper catalog alternatives.
| Model | Provider | Type | Input | Output |
|---|---|---|---|---|
| gpt-5-nano | OpenAI | chat | 0.0500 Token / 1M tokens | 0.4000 Token / 1M tokens |
| gpt-5-nano-2025-08-07 | OpenAI | chat | 0.0500 Token / 1M tokens | 0.4000 Token / 1M tokens |
| gpt-4.1-nano | OpenAI | chat | 0.1000 Token / 1M tokens | 0.4000 Token / 1M tokens |
| gpt-4.1-nano-2025-04-14 | OpenAI | chat | 0.1000 Token / 1M tokens | 0.4000 Token / 1M tokens |
| sora-2 | OpenAI | video | 0.1000 Token / 1M tokens | — |
A quick read of the model identity, commercial setup, and access footprint.
Published rates, tier transitions, and modality-specific surcharges in the current catalog entry.
| Pricing | Billing mode |
|---|---|
| Prompt | $0.0014/1M tokens |
Hourly usage, latency, reliability, and throughput for this model.
Top 10 AI coding agents using this model during the last 15 days.
Top 10 official SDKs and language HTTP clients using this model during the last 15 days.
| text-embedding-ada-002 | OpenAI | embedding | 0.1000 Token / 1M tokens | — |