What are the embedding dimensions for text-embedding-3-large?

text-embedding-3-large supports configurable embedding dimensions. Check the current API documentation for the available dimension options and choose the one that fits your use case.

When was text-embedding-3-large released, and is it still maintained?

text-embedding-3-large is listed with catalog status stable. The recorded release date is 2024-01-25. Check the model page for deprecation notices before you build a long-lived integration on it.

What is text-embedding-3-large best used for?

text-embedding-3-large is best used for semantic search, clustering, recommendations, and other tasks requiring high-quality text similarity measurements across multiple languages.

What is the max output length for text-embedding-3-large?

text-embedding-3-large has no token-based output limit: it returns fixed-size embedding vectors, and the output size follows the embedding dimension you choose.

What is the rate limit for text-embedding-3-large?

text-embedding-3-large rate limits vary by your MixRoute subscription plan. Check your plan details in the console for requests per minute (RPM) and tokens per minute (TPM) limits. Run a small load test before production to confirm your effective quota.

How much does it cost to embed a million records with text-embedding-3-large?

text-embedding-3-large is billed per input token at 0.13 USD per 1,000,000 tokens. One million records cost the listed rate multiplied by the total tokens those records produce; the default output dimension is 3,072.

Can you call text-embedding-3-large with the OpenAI SDK you already use?

Yes. text-embedding-3-large is reachable through an OpenAI-compatible endpoint, so an existing OpenAI SDK client works after pointing the base URL at MixRoute and setting the model parameter to text-embedding-3-large . Keep your current request and response handling.

Model detail

text-embedding-3-large

Provided by OpenAI

Pay-as-you-go

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.

Model specs

Model ID: text-embedding-3-large

Context length: 8.191K
Max output: –
I/O modalities
Released: 2025-10

API endpoints

One MixRoute gateway, OpenAI-compatible

OpenAI-compatible /v1/chat/completions POST

Pricing

Flat rate, unit: /1M Tokens

Input

$0.1300 /1M Tokens

Completion

$0.1300 /1M Tokens

Selection summary

Quickly judge whether it fits your workload

What is this model good for?

OpenAI's most capable embedding model for both english and non-english tasks

What should you check before using it?

Confirm vector dimensions and token limits

text-embedding-3-large supports the OpenAI SDK. Knowledge cutoff: 2024-01. Released 2024-01-25. It is billed at 0.13 USD per 1M tokens. Test a representative workload before production.

Why use it through MixRoute?

Swap the base URL, keep the text-embedding-3-large client

MixRoute serves text-embedding-3-large on the OpenAI-compatible endpoint /v1/chat/completions; point your existing client at https://api.mixroute.ai/v1 with the model ID text-embedding-3-large and re-run your integration tests.

Capabilities & compatibility

Unconfirmed capabilities stay "Unknown," no guesses

OpenAI SDK

Call text-embedding-3-large through MixRoute's OpenAI-compatible endpoint.

EX Change base_url to https://api.mixroute.ai/v1; everything else follows the OpenAI style.

Token cost estimator

Live estimate from this page's pricing, not an actual bill

Input tokens Max per request 8.191K

Output tokens

Requests / month

Cache hit rate –

This model has no cache-read price; caching is not counted

FAQ

Use the model ID text-embedding-3-large through the compatible embeddings endpoint. You can configure the embedding dimensions to balance accuracy and storage.

Get started

01

Create an API key

Generate a key in the Console; one key calls every model.
02

Set the base URL

Fully OpenAI SDK-compatible; just swap the URL to connect.

https://api.mixroute.ai/v1
03

Specify the model ID

In the request's model field, enter:

text-embedding-3-large

Create an API key

New users get $5 in free credits

Test this model and alternate routes with the same request format

Start from a real workload, then let quality, total cost, and failure conditions decide whether to send production traffic.

Create an API key View integration docs