Embed English v3.0
cohere-embed-english-v3-0
Last refreshed 2026-05-16. Next refresh: weekly.
Embed English v3.0 is worth evaluating for general LLM work when its provider route and context window match the workload.
Decision context: Coding task fit, 1 tracked provider route, and research from 2026-01-01.
Use it for
- Teams evaluating general LLM work
- Workloads that can use a 512 context window
- Buyers comparing 1 tracked provider route
Do not use it for
- Strict JSON or tool-calling flows
Cheapest output
-
Microsoft Foundry per 1M tokens
Provider routes
1
Tracked API hosts
Quality / dollar
Unknown
No task benchmark coverage yet
Freshness
2026-01-01
Researched 137d ago
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| Microsoft Foundry | $0.100 | - | ServerlessPartial |
Benchmark peer barsfor Coding
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
About
English-only embedding model supporting text and image inputs. Produces 1024-dimensional embeddings optimized for semantic search, classification, and clustering. Supports multiple similarity metrics (Cosine, Dot Product, Euclidean Distance).
Embed English v3.0 has a 512-token context window.
