Cohere Embed v3vsAya Expanse
Cohere vs Cohere — Side-by-side model comparison
Head-to-Head Comparison
| Metric | Cohere Embed v3 | Aya Expanse |
|---|---|---|
| Provider | ||
| Arena Rank | — | — |
| Context Window | 512 tokens | 128K |
| Input Pricing | $0.10/1M tokens/1M tokens | Free/1M tokens |
| Output Pricing | N/A (embeddings)/1M tokens | Free/1M tokens |
| Parameters | Undisclosed | 32B |
| Open Source | No | Yes |
| Best For | Search, RAG, semantic similarity, clustering | Multilingual (23 languages), research |
| Release Date | Nov 2, 2023 | Oct 24, 2024 |
Cohere Embed v3
Cohere Embed v3 is one of the leading text embedding models, supporting over 100 languages with state-of-the-art retrieval performance. It produces dense vector representations of text that power semantic search, RAG pipelines, and classification systems. The model offers specialized embedding types for search queries vs documents, optimizing retrieval accuracy for enterprise applications.
View Cohere profile →Aya Expanse
Aya Expanse is Cohere's multilingual open-source model supporting 23 languages, developed through the Cohere For AI research initiative with contributions from researchers worldwide. The 32B parameter model demonstrates strong performance across diverse languages and tasks, with particular attention to lower-resource languages that are often underserved by mainstream AI models. As an open-source contribution, Aya Expanse aims to democratize access to high-quality multilingual AI and enable researchers globally to build on its capabilities for their specific linguistic and cultural contexts.
View Cohere profile →Key Differences: Cohere Embed v3 vs Aya Expanse
Aya Expanse supports a larger context window (128K), allowing it to process longer documents in a single request.
Aya Expanse is open-source (free to self-host and fine-tune) while Cohere Embed v3 is proprietary (API-only access).
When to use Cohere Embed v3
- +Quality matters more than cost
- +You prefer a managed API without infrastructure overhead
- +Your use case involves search, rag, semantic similarity, clustering
When to use Aya Expanse
- +Budget is a concern and you need cost efficiency
- +You need to process long documents (128K context)
- +You need to self-host or fine-tune the model
- +Your use case involves multilingual (23 languages), research
The Verdict
Aya Expanse wins our head-to-head comparison with 4 out of 5 category wins. It's the stronger choice for multilingual (23 languages), research, though Cohere Embed v3 holds an edge in search, rag, semantic similarity, clustering.
Last compared: March 2026 · Data sourced from public benchmarks and official pricing pages