Request batching is distinct from asynchronous Embed Jobs. Token limits still apply per input.
Embedding controls
input_type: search_document, search_query, classification, clustering or image, truncate: END (default), START or NONE, max_tokens: per-input truncation control, priority: lower values receive higher prioritySource for Embedding controls (opens in a new tab)
These are embedding API controls, not text-generation sampling parameters.
Access & pricing
Prices belong to an endpoint and billing tier. A provider listing does not guarantee access for every account or region.
Provider catalog lists this selector. Hosting support and regional access are separate from Cohere API capabilities.
Regions
Not collected
Prices retain their published currencies and billing units below.
Published billing units · original currency · observed 14 Oct 2026
Category
Usage
Rate
Unit
Embeddings
Text input1
$0.10
1M text tokens
Embeddings
Image input2
$0.0001
image
Rate conditions
US East (N. Virginia); AWS price-map publication 2026-10-12T08:40:08Z. Published Bedrock text embedding rate. Not a direct Cohere API rate; output vectors do not incur a generated-token charge.
US East (N. Virginia); AWS price-map publication 2026-10-12T08:40:08Z. Published Bedrock image embedding rate. Do not convert to a per-image-token rate or apply it to the Light variants.
OCI on-demand retired on 2026-09-30; creation of new dedicated base deployments retired on the same date. Existing dedicated/custom deployments may continue under Oracle’s retirement policy. This does not retire the direct Cohere API model.
OCI dedicated base-model creation retired on 2026-09-30. Exact on-demand retirement for this image selector was not listed in the reviewed table; current availability must be checked. Existing dedicated/custom deployments have exceptions.
Regions
Not collected
Endpoint pricing has not been collected. Check the provider for applicable rates.
Data & enterprise terms
Retention, training use, regional processing and enterprise terms have not been summarized for this endpoint.
Caching
Caching can reuse earlier input processing. Availability, lifetime and billing depend on the endpoint. A cache hit still generates a new response.
01 / INITIAL INPUTProcess & retain
The system processes eligible input and retains reusable state.
02 / LATER REQUESTCheck available state
Reuse depends on matching input, session state and the cache policy.
03 / CACHE HITReuse & generate
Reusing state can reduce repeated work. Any charges follow the billing rules below.
Cohere API
embed-english-v3.0
Not verified
No model-specific embedding cache contract verified. A shared API cached_tokens schema field is insufficient evidence of support.
How it works
Not collected
Minimum reusable input
Not collected
Lifetime & refresh
Not collected
How to enable it
Not collected
Usage fields
Not collected
Billing rules
Not collected
Limits & data boundaries
Not collected
No verified cache rate for this endpoint. An empty rate is not a zero charge.
Caching reviewed 14 Oct 2026
Amazon SageMaker
Not verified
No model-specific embedding cache contract verified. A shared API cached_tokens schema field is insufficient evidence of support.
How it works
Not collected
Minimum reusable input
Not collected
Lifetime & refresh
Not collected
How to enable it
Not collected
Usage fields
Not collected
Billing rules
Not collected
Limits & data boundaries
Not collected
No verified cache rate for this endpoint. An empty rate is not a zero charge.
Caching reviewed 14 Oct 2026
Amazon Bedrock
cohere.embed-english-v3
Not verified
No model-specific embedding cache contract verified. A shared API cached_tokens schema field is insufficient evidence of support.
How it works
Not collected
Minimum reusable input
Not collected
Lifetime & refresh
Not collected
How to enable it
Not collected
Usage fields
Not collected
Billing rules
Not collected
Limits & data boundaries
Not collected
No verified cache rate for this endpoint. An empty rate is not a zero charge.
Caching reviewed 14 Oct 2026
Microsoft Foundry
Not verified
No model-specific embedding cache contract verified. A shared API cached_tokens schema field is insufficient evidence of support.
How it works
Not collected
Minimum reusable input
Not collected
Lifetime & refresh
Not collected
How to enable it
Not collected
Usage fields
Not collected
Billing rules
Not collected
Limits & data boundaries
Not collected
No verified cache rate for this endpoint. An empty rate is not a zero charge.
Caching reviewed 14 Oct 2026
Oracle OCI Generative AI
cohere.embed-english-v3.0
Not verified
No model-specific embedding cache contract verified. A shared API cached_tokens schema field is insufficient evidence of support.
How it works
Not collected
Minimum reusable input
Not collected
Lifetime & refresh
Not collected
How to enable it
Not collected
Usage fields
Not collected
Billing rules
Not collected
Limits & data boundaries
Not collected
No verified cache rate for this endpoint. An empty rate is not a zero charge.
Caching reviewed 14 Oct 2026
Oracle OCI Generative AI
cohere.embed-english-image-v3.0
Not verified
No model-specific embedding cache contract verified. A shared API cached_tokens schema field is insufficient evidence of support.
How it works
Not collected
Minimum reusable input
Not collected
Lifetime & refresh
Not collected
How to enable it
Not collected
Usage fields
Not collected
Billing rules
Not collected
Limits & data boundaries
Not collected
No verified cache rate for this endpoint. An empty rate is not a zero charge.
Caching reviewed 14 Oct 2026
What the measurements say
No benchmark observations have been added for this model. We do not turn a vendor description into a performance score.
Latency and throughput depend on the host, request size, reasoning settings and load. There is no measured speed or global usage figure in this record.
The record behind the model
Why it is included
The provider’s exact-model repository publishes tokenizer/configuration files, not model weights. Its model card calls it a tokenizer repository and directs inference to the Cohere API, SageMaker or sales-arranged private deployment. Public tokenizer files do not make the model open-weight.