Benchable
Text input
Text output
Author's Description
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.
Key Specifications
Cost
$
Context
8K
Released
Oct 30, 2025
Supported Parameters
This model supports the following parameters:
Top P
Logit Bias
Structured Outputs
Frequency Penalty
Seed
Presence Penalty
Response Format
Max Tokens
Stop
Top Logprobs
Temperature
Logprobs
Features
This model supports the following features:
Structured Outputs
Response Format
Model Pricing
Current Pricing
| Feature | Price (per 1M tokens) |
|---|---|
| Prompt | $0.13 |
| Completion | $0 |
Price History
Available Endpoints
| Provider | Endpoint Name | Context Length | Pricing (Input) | Pricing (Output) |
|---|---|---|---|---|
|
OpenAI
|
OpenAI | openai/text-embedding-3-large | 8K | $0.13 / 1M tokens | $0 / 1M tokens |
Benchmark Results
| Benchmark | Category | Reasoning | Strategy | Free | Executions | Accuracy | Cost | Duration |
|---|
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