OpenAI: Text Embedding 3 Large provider comparison

openai/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...

Endpoints:: 2
Context:: 8.2K
Input:: text
Output:: embeddings

Visual comparison

Endpoint pricing chart

Compare published endpoint pricing visually.

Effective price by endpoint

USD per unit for prompt. Lower is better.

Only directly comparable published units are charted.

Server-rendered comparison

Provider endpoints

Prices are shown only in the units published by OpenRouter; cross-unit rankings are intentionally omitted. Missing speed data never removes an endpoint.

Endpoint comparison for OpenAI: Text Embedding 3 Large
Provider / route	Current pricing	Speed measurements	Endpoint details
Provider / route OpenAI`openai`	Current pricing $0.00000013 per unit (prompt) Free per unit (completion)	Speed measurements 500-token response Not applicable Response starts Insufficient recent data Output speed Insufficient recent data	Endpoint details Uptime (30 min) 99.98% Context 8.2K Model format unknown Max output N/a 12 parameters frequency_penalty, logit_bias, logprobs, max_tokens, presence_penalty, response_format, seed, stop, structured_outputs, temperature, top_logprobs, top_p
Provider / route Azure`azure`	Current pricing $0.00000013 per unit (prompt) Free per unit (completion)	Speed measurements 500-token response Not applicable Response starts Insufficient recent data Output speed Insufficient recent data	Endpoint details Uptime (30 min) 100.00% Context 8.2K Model format unknown Max output N/a 4 parameters max_completion_tokens, max_tokens, temperature, top_p

Endpoint data fetched Jul 15, 2026, 11:17 PM UTC.

Text Embedding 3 Large deployment guide

How to choose a Text Embedding 3 Large inference provider

Text Embedding 3 Large is indexed here as a embeddings model by OpenAI, with 2 provider endpoints from OpenAI, Azure. The comparison preserves each exact OpenRouter routing tag so pricing and performance observations can be connected to the route an application would actually request.

Match the endpoint to the workload

The model publishes a 8.2K-token context window. It accepts text input and returns embeddings output. 13 distinct supported parameters appear across the listed routes. Confirm limits on the specific endpoint rather than assuming every host exposes the same configuration.

Compare embeddings billing units directly

At least one unit is published consistently across the listed endpoints, allowing a direct price chart for prompt. Other charges remain in the table using OpenRouter’s exact billing labels.

Verify route format and availability

Published endpoint formats include unknown. Availability, rate limits, and regional support can change independently of catalog pricing, so confirm the selected routing tag before production deployment.