ShipSquad

text-embedding-3-large Review 2026

OpenAIEmbedding Model2024-014.5/5

Overview

OpenAI's most capable text embedding model producing high-dimensional vectors for semantic search, clustering, and retrieval. Features flexible dimensionality and strong multilingual performance.

ProviderOpenAI
Context Window8K tokens
Pricing$0.13 per 1M tokens

Capabilities

  • Text embedding generation
  • Semantic search
  • Clustering
  • Classification
  • Anomaly detection
  • Retrieval augmentation

Pricing

$0.13 per 1M tokens

Pros & Cons

Pros

  • +Flexible dimensionality reduction without significant quality loss
  • +Strong multilingual embedding quality across many languages
  • +Low cost per token for high-volume embedding workloads
  • +Excellent performance on MTEB benchmark suite

Cons

  • -8K token limit requires chunking strategies for long documents
  • -Proprietary model cannot be self-hosted
  • -Embedding space not compatible with other providers' models

Frequently Asked Questions

What is text-embedding-3-large?

OpenAI's most capable text embedding model producing high-dimensional vectors for semantic search, clustering, and retrieval. Features flexible dimensionality and strong multilingual performance.

How much does text-embedding-3-large cost?

text-embedding-3-large pricing: $0.13 per 1M tokens

What is the context window for text-embedding-3-large?

text-embedding-3-large supports a context window of 8K tokens.

When was text-embedding-3-large released?

text-embedding-3-large was released on 2024-01 by OpenAI.

Further Reading

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