Embed / Rerank is a Retrieval models from Cohere (Canada / United States).
One-line fit: best used for Production RAG quality.
Key specifications
| Provider | Cohere |
|---|---|
| Model | Embed / Rerank |
| Type | Retrieval models |
| Context window | N/A |
| Pricing (indicative) | API |
| Company category | Enterprise LLM |
| Region | Canada / United States |
| Official site | https://cohere.com |
Benchmarks and public standing
Top retrieval leaderboards historically
Treat scores as directional. SWE-bench, Terminal-Bench, LMSYS Arena, Artificial Analysis, and vendor cards use different harnesses and are not always comparable 1:1. Re-check the latest official model card before decisions.
What this model is good at
Production RAG quality
This aligns with Cohere’s broader strengths:
- Enterprise RAG
- Embeddings and rerank
- Secure VPC deploys
- Multilingual business text
Limitations and watch-outs
Not generative flagship chat
- Rate limits, regional availability, and data retention policies vary by plan.
- Agent harness quality (Cursor, Claude Code, Codex, custom tools) can change outcomes more than raw model Elo.
- Open-weight availability (if any) is separate from hosted API quality and safety filters.
Ideal users
- Product engineers shipping features that match: Production RAG quality
- Teams standardizing on the Cohere ecosystem
- Agent builders who need a Retrieval models
When to pick something else
- Cheaper volume: compare lower tiers from the same lab or open Chinese/EU alternatives.
- Maximum hard SWE thoughtfulness: compare Claude Fable-class and other coding flagships.
- Giant multimodal corpora / Workspace: compare Gemini-class models.
- Self-host / open weights: Llama, Qwen, DeepSeek, GLM, Mistral open lines.
Parent company
Cohere – Enterprise-focused LLMs and RAG (Command, Embed, Rerank) for secure business search.
Related models from Cohere
- Command R / R+ / Aya lineage – Enterprise LLM
Data is curated for AIForumSphere model directory mid-2026 directional figures.
