openai·embedding
text-embedding-3-large
openai/text-embedding-3-large
OpenAI's large embedding model — 3072-dim, very strong semantic search.
At a glance
- · $0.13 input / $0.00 output per 1M tokens (provider list price, billed in credits)
- · Context window: 8,191 tokens
- · OpenAI-compatible — model: "openai/text-embedding-3-large" (provider: openai)
- · Best for: 3072 dimensions — top accuracy on MTEB benchmarks
Strengths
- +3072 dimensions — top accuracy on MTEB benchmarks
- +Dimension can be shortened via API (Matryoshka) — save storage without re-embedding
- +Multilingual, strong on cross-language retrieval
Weaknesses
- −Pricier than 3-small, often with no noticeable quality edge on small corpora
- −Full 3072-dim is storage-intensive
Use cases
- →Semantic search over large knowledge bases
- →High-quality RAG pipelines
- →Cross-language retrieval (e.g. English query over German corpus)
Alternatives in the catalog
How to call it
Drop-in OpenAI-compatible. Just swap the `model` string and you're using this model.
curl https://www.getmorecredits.com/v1/embeddings \
-H "Authorization: Bearer $GMC_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/text-embedding-3-large",
"input": "GetMoreToken: one API for 230+ AI models."
}'Good for
Frequently asked questions
How much does text-embedding-3-large cost?⌄
Input is $0.13 per million tokens; output is $0.00 per million tokens — provider list price. On getmorecredits.com you pay in credits, no subscription, no minimum spend.
What's the context window of text-embedding-3-large?⌄
text-embedding-3-large accepts up to 8,191 input tokens. That fits long conversations and medium documents into a single call.
Is text-embedding-3-large OpenAI-compatible?⌄
Yes. On getmorecredits.com you call text-embedding-3-large with the same request shape as OpenAI: POST /v1/embeddings with "model": "openai/text-embedding-3-large". Existing OpenAI SDKs (Python, Node, etc.) work by changing the base URL and API key.