embed-v5.0-provsvoyage-context-4
Both embedding models, compared at each maker’s own API list prices. Every figure links to its source.
Key differences
Dimensions
2,048 An Overview of Cohere's Models · as of Oct 30, 2026
1,024 Incrustaciones de fragmentos contextualizados - Voyage AI por MongoDB - MongoDB Docs · as of Nov 4, 2026
Max input
128,000 An Overview of Cohere's Models · as of Oct 30, 2026
120,000 Contextualized Chunk Embeddings - Voyage AI by MongoDB - MongoDB Docs · as of Oct 31, 2026
These differences use verified vendor specifications or each maker’s official API on the same region, currency, meter and billing conditions. Different conditions remain side by side in the full table; they do not establish which model is cheaper. Declared features describe support, not measured quality or a recommendation. Missing evidence does not mean a feature is unsupported.
Full comparison
| embed-v5.0-pro Cohere | voyage-context-4 Voyage AI | |
|---|---|---|
| Overview | ||
| Released | Not stated | Jun 30, 2026 |
| Specs | ||
| Dimensions | 2,048 | 1,024 |
| Shortest vector | 256 | 256 |
| Max input | 128K | 120K |
| Input modalities | Text, Image, PDF | Not stated |
| Inputs per request | 96 | Not stated |
| Languages | 100 | Not stated |
| Pricing | ||
| Price per 1M input tokens | $0.12 | $0.12 |
Headline prices may come from different channels, regions or tiers. Check each source before choosing a model; missing facts stay blank.
Model details and sources
- embed-v5.0-pro → Available
- voyage-context-4 → Available