Cohere releases Embed 5
Embed 5 released — a family of embedding models in two tiers, Pro and Fast. Both tiers have a 128K-token context, variable output dimensions of 2048, 1536, 1024, 768, 512 and 256 (Matryoshka), more than 100 languages, text, image and fused text+image input, and float, int8 and binary embedding formats. Company-reported figures: ViDoRe V3 (enterprise documents) Pro 85.8 and Fast 84.5, FinanceBench 80.1, FinQA 90.0, ViDoRe Finance 85.0, fused text-image retrieval average 82.3, page-image financial dataset 77.0, and an average of 77 across German, French, Spanish, Italian and Russian (Farsi +13, Telugu +12, Hindi +12). The two tiers share an embedding space, so documents indexed with Pro can be queried with Fast without reindexing ("one index, two models"). Per 1M tokens: Pro $0.12, Fast $0.08 (images $0.40 for both). Available on the Cohere API, Model Vault, Microsoft Foundry, Amazon SageMaker and North.
Why it matters
A case of the competitive focus of embedding models moving from scores to operating costs. The design in which tiers share an embedding space aims to eliminate reindexing costs — the biggest barrier to switching models in large-scale RAG — and if it works, the replacement cycle for embedding models will shorten.
Source — Primary sources first; secondary reports are labelled “Press”
Officialcohere.comhttps://cohere.com/blog/embed-5Added in Week 41, 2026 · See that week