Model comparison

vs

text-embedding-3-large vs voyage-4-large

Compared on price, indexing cost, vector size and input limits.

The short answer

  • Voyage 4 Large is cheaper: $0.12/M against $0.13/M.
  • Voyage 4 Large takes longer inputs (32k tokens against 8k tokens), so it needs less chunking.
  • Voyage 4 Large returns smaller vectors (1024 against 3072 dimensions), which cuts index storage by 67%.

Side-by-side specs

Spectext-embedding-3-largevoyage-4-large
ProviderOpenAIVoyage AI
Price$0.13/M$0.12/M
Max input8k tokens32k tokens
Default dimensions3,0721,024
Storage per 1M vectors12.3 GB4.1 GB
AcceptsTextText
MultilingualYesYes
WeightsClosedClosed

Same work, both models

Workloadtext-embedding-3-largevoyage-4-large
Index 10,000 help articles~800 tokens each, 8M tokensOpenAI Embedding 3 Large costs 1.1× as much$1.04$0.96
Index a 1M-line codebase~10 tokens a line, 10M tokens$1.30$1.20
Embed 1M search queries~20 tokens each, 20M tokens$2.60$2.40

At listed rates, before the 5% platform fee. Re-embedding an index costs the same again.

When to pick which

text-embedding-3-large

text-embedding-3-large is the larger of OpenAI's two third-generation text embedding models, returning 3072-dimension vectors by default. It sits above text-embedding-3-small, which costs less per token and returns 1536-dimension vectors.

Pick it if

  • retrieval quality matters more than cost per token
  • you want shorter vectors via the dimensions parameter, for example 256
  • you embed non-English as well as English text

Skip it if

  • text-embedding-3-small is accurate enough at a lower price
  • you need to embed images; it accepts text only

voyage-4-large

Voyage 4 Large is the top tier of Voyage AI's Voyage 4 embedding series, a mixture-of-experts model for general-purpose and multilingual retrieval. It sits above voyage-4 and voyage-4-lite, and all three share one embedding space.

Pick it if

  • retrieval quality matters more than cost per token
  • you want to embed documents with it and run queries on voyage-4-lite
  • you need multilingual retrieval or 256-2048 dimension embeddings

Skip it if

  • voyage-4 or voyage-4-lite is accurate enough at a lower price
  • you are indexing source code; voyage-code-4 targets code retrieval

FAQ

Which is cheaper, OpenAI Embedding 3 Large or Voyage 4 Large?

Voyage 4 Large is cheaper: $0.12/M against $0.13/M.

Which handles longer documents?

Voyage 4 Large takes longer inputs (32k tokens against 8k tokens), so it needs less chunking.

Can I switch from OpenAI Embedding 3 Large to Voyage 4 Large without re-indexing?

No. Vectors from different embedding models are not comparable, so a switch means re-embedding the whole corpus.

Try either model

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Prices from the catalog of 2026-10-22